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About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.About the Role As an Accounting Expert, you will be instrumental in enhancing the capabilities of our cutting-edge technologies by providing high-quality input and labels using specialized software. Your role involves collaborating closely with our technical team to support the training of new AI tasks, ensuring the implementation of innovative initiatives. You'll contribute to refining annotation tools and selecting complex problems from corporate accounting domains, with a focus on financial reporting, consolidation, internal controls, and GAAP compliance where your expertise can drive significant improvements in model performance. This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. AI Tutor’s Role in Advancing xAI’s Mission As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in corporate accounting. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities Use proprietary software applications to provide input/labels on defined projects.   Support and ensure the delivery of high-quality curated data.   Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.   Interact with the technical staff to help improve the design of efficient annotation tools.   Choose problems from corporate accounting fields that align with your expertise, providing rigorous solutions and model critiques where you can confidently provide detailed solutions and evaluate model responses.   Regularly interpret, analyze, and execute tasks based on given instructions.   Key Qualifications Must have 3+ years of Big 4 public accounting experience (audit/assurance) on corporate or SEC clients, or an equivalent senior corporate accounting role (e.g., Controller, Assistant Controller, or Technical Accounting Manager at a public company or large private enterprise with complex GAAP reporting).   Must possess a Master's or PhD in Accounting (corporate focus) or equivalent as a licensed CPA.   Proficiency in reading and writing, both in informal and professional English.   Strong ability to navigate various corporate accounting information resources, databases, and online resources (e.g., FASB codification, SEC EDGAR, 10-K/10-Q filings, ERP systems).   Outstanding communication, interpersonal, analytical, and organizational capabilities.   Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material.   Strong passion for and commitment to technological advancements and innovation in corporate accounting.  Preferred Qualifications 5+ years at a Big 4 firm or in a senior corporate controllership role, with direct involvement in SEC reporting, SOX 404, or complex consolidations.   Experience drafting or reviewing 10-K/10-Q footnotes, MD&A, or technical accounting memos.   Possesses experience with at least one publication in a reputable accounting journal or outlet.   Teaching experience as a professor   Location & Other Expectations This position is based in Palo Alto, CA, or fully remote.   The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation.   If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time.   We are unable to provide visa sponsorship.   Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter.   For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.   Compensation $45/hour - $100/hour The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location. Benefits: Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

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About UsHarmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.About the RoleAs a Data Engineer on the Foundational team, you will serve as the "plumber" for deep learning, building the massive, high-performance data infrastructure required to power our foundational models. Based in Paris, you will manage terabytes—and eventually petabytes—of raw, unstructured, and noisy video data (EO and IR). Your mission is to ensure our ML engineers spend their time designing architectures, not waiting for data loaders or wrangling corrupted files.ResponsibilitiesMulti-Modal Ingestion Pipeline: Build ETL/ELT pipelines to extract, decode, and store raw Electro-Optical (EO) and Infrared (IR) video from field logs into highly optimised formats like WebDataset, TFRecords, or Parquet.Sensor Synchronisation & Alignment: Develop algorithms to programmatically synchronise EO and IR frames temporally and spatially to provide paired inputs for model training.High-Throughput Data Loading: Architect storage-to-GPU pipelines to ensure multi-node training clusters maintain >90% GPU utilisation without I/O bottlenecks.Distributed Processing: Write and optimise distributed data processing jobs using tools like Apache Spark, Ray, or Apache Beam to process thousands of hours of tactical video logs.Data Quality & Versioning: Implement automated quality checks to filter corrupted or blank frames and maintain 100% reproducible training runs through robust versioning and lineage tracking.Infrastructure Evaluation: Assess and implement advanced storage solutions (e.g., MinIO, S3 tiering) to manage growing datasets while optimising for cost and latency.Candidate RequirementsEducational Background: A BS or MS in Computer Science, Software Engineering, or Distributed Systems is highly preferred. Deep knowledge of operating systems, networking, and parallel computing is essential.Technical Experience: 5-6+ years of experience building and maintaining terabyte-scale pipelines for unstructured data (video, images, or point clouds).Performance Optimisation: Proven track record of maximising multi-node GPU utilisation and optimising data loaders for frameworks like PyTorch or JAX.Tooling Expertise: Strong command of distributed computing tools (Spark, Ray, Beam) and ML data versioning tools (DVC, Apache Iceberg, or Pachyderm).Adaptability & Ownership: A systems-thinker who thrives in a fast-paced startup environment and views messy data as an engineering problem to be solved via automation.Commitment: 100% dedication to Harmattan AI’s mission of providing a defensive edge to allied nations through ethical, high-impact technologyWe look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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About UsHarmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.About the RoleWe are looking for a Computer Vision Engineer to join our Machine Learning and Computer Vision team. This role is crucial for developing core technical components across various robotics/aerospace projects.ResponsibilitiesResearch & Data Preparation: Conduct research on state-of-the-art Computer Vision methodologies. Participate in the creation and curation of training and validation datasets. Perform statistical analyses and develop visualization tools to ensure data quality.Algorithm Development & Optimization: Build and refine training pipelines and metrics to enhance model performance.Develop and optimize Computer Vision algorithms for multiple robotics/aerospace projects.Deployment & Integration: Implement ML/CV models into production-ready environments. Ensure seamless integration with Harmattan AI’s systems and conduct rigorous code reviews.Validation & Monitoring: Test algorithms in real-world environments and develop monitoring tools. Track model performance and continuously improve deployed solutions.Cross-Team Collaboration: Work closely with software and simulation teams to align development with system requirements. Communicate findings effectively to stakeholders.Candidate RequirementsEducational Background: A degree from a top-tier engineering school or university (Master’s degree in Computer Science or related field, PhD is a plus)Technical Expertise: Strong mathematical foundations, coding skills (Python, C++ is a plus) and hands-on ML/CV project experience. Experience in top AI companies is a huge plus.Passion for ML: Enthusiasm for Machine Learning and Computer Vision. Strong Communication & Teamwork: Ability to collaborate effectively with diverse teamsCommitment: 100% dedication to Harmattan AI’s mission, vision, and ambitious growth plans, ready to go the extra mile to ensure operational excellence.We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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About MagicalMagical is an agentic automation platform bringing state-of-the-art AI to healthcare, delivering AI agents that actually work in production.We're building "AI employees" that automate the repetitive, time-consuming workflows that slow teams down. Our focus is healthcare – a $4 trillion industry buried in administrative complexity – where we automate claims processing, prior authorizations, and eligibility checks, enabling providers to focus on patient care.Our TractionThe shift to agentic automation in healthcare is inevitable, and we're leading it:Dramatic acceleration in revenue growth with customers expanding into new workflows before renewal7-day proof-of-concepts that demonstrate real value fast, in an industry where months is the normSelf-healing automations with production-grade reliability at scale, where most competitors fail to launchUnlike many AI companies making bold promises, we ship reliable solutions that deliver measurable results. We're backed by Greylock, Coatue, and Lightspeed with $41M raised. Our founder, Harpaul Sambhi, is a second-time founder who successfully sold his first company to LinkedIn.About the RoleAs our Engineering Manager on our Autonomous team, you will lead and scale a high-calibre team of engineers dedicated to defining the future of AI agent development, pushing the boundaries of AI and backend systems.You are deeply passionate about the craft of management and find genuine fulfillment in helping engineers grow their careers. You bring the technical credibility required to navigate complex architectural discussions and translate deep technical challenges into clear business strategies. In this role, you will serve as the essential bridge between product vision and technical execution.This is a hybrid role with 2 days per week in our Toronto office.In this role, you willOversee the technical roadmap for the Autonomous team, translating architectural complexity into clear product strategiesMentor a diverse group of engineers, ranging from product-focused builders to specialized Staff Engineers, and actively support their professional growthPartner closely with Product and Design to ensure our agent-building tools remain intuitive while supporting deep technical capabilitiesChampion a "show > tell" culture by ensuring the team ships rapidly and maintains a high bar for both technical stability and user experienceClear technical and operational roadblocks to ensure the team operates with high agency and clarityYour background looks something like thisHave a proven track record of leading and scaling engineering teams in fast-paced, high-growth environments.Possess the technical background necessary to critically evaluate complex trade-offs and provide strategic direction on complex system designsExperience navigating the balance between long-term technical health and the immediate needs of a rapidly evolving productEmbody a servant-leadership philosophy, with a primary focus on the success of the team and individual growthHigh degree of agency: you thrive in ambiguity and proactively improve processes or solve bottlenecks without much outside inputStrong business acumen and a genuine interest in how technical decisions impact the customer and the company's successEven betterPrior experience building AI-powered products or developer toolsA sharp eye for design and product qualityExperience with real-time interfaces, data visualization, or collaborative editingUnderstanding of agent systems, LLMs, or evaluation frameworksTrack record of building products that balance power and simplicityWe're building the best self-serve agentic automation platform for the healthcare industry and we're just getting started. Come join us.

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About MagicalMagical is an agentic automation platform bringing state-of-the-art AI to healthcare, delivering AI agents that actually work in production.We're building "AI employees" that automate the repetitive, time-consuming workflows that slow teams down. Our focus is healthcare – a $4 trillion industry buried in administrative complexity – where we automate claims processing, prior authorizations, and eligibility checks, enabling providers to focus on patient care.Our TractionThe shift to agentic automation in healthcare is inevitable, and we're leading it:Dramatic acceleration in revenue growth with customers expanding into new workflows before renewal7-day proof-of-concepts that demonstrate real value fast, in an industry where months is the normSelf-healing automations with production-grade reliability at scale, where most competitors fail to launchUnlike many AI companies making bold promises, we ship reliable solutions that deliver measurable results. We're backed by Greylock, Coatue, and Lightspeed with $41M raised. Our founder, Harpaul Sambhi, is a second-time founder who successfully sold his first company to LinkedIn.About the RoleAs our Engineering Manager on our Autonomous team, you will lead and scale a high-calibre team of engineers dedicated to defining the future of AI agent development, pushing the boundaries of AI and backend systems.You are deeply passionate about the craft of management and find genuine fulfillment in helping engineers grow their careers. You bring the technical credibility required to navigate complex architectural discussions and translate deep technical challenges into clear business strategies. In this role, you will serve as the essential bridge between product vision and technical execution.This is a hybrid role with 2 days per week in our San Francisco office.In this role, you willOversee the technical roadmap for the Autonomous team, translating architectural complexity into clear product strategiesMentor a diverse group of engineers, ranging from product-focused builders to specialized Staff Engineers, and actively support their professional growthPartner closely with Product and Design to ensure our agent-building tools remain intuitive while supporting deep technical capabilitiesChampion a "show > tell" culture by ensuring the team ships rapidly and maintains a high bar for both technical stability and user experienceClear technical and operational roadblocks to ensure the team operates with high agency and clarityYour background looks something like thisHave a proven track record of leading and scaling engineering teams in fast-paced, high-growth environments.Possess the technical background necessary to critically evaluate complex trade-offs and provide strategic direction on complex system designsExperience navigating the balance between long-term technical health and the immediate needs of a rapidly evolving productEmbody a servant-leadership philosophy, with a primary focus on the success of the team and individual growthHigh degree of agency: you thrive in ambiguity and proactively improve processes or solve bottlenecks without much outside inputStrong business acumen and a genuine interest in how technical decisions impact the customer and the company's successEven betterPrior experience building AI-powered products or developer toolsA sharp eye for design and product qualityExperience with real-time interfaces, data visualization, or collaborative editingUnderstanding of agent systems, LLMs, or evaluation frameworksTrack record of building products that balance power and simplicityWe're building the best self-serve agentic automation platform for the healthcare industry and we're just getting started. Come join us.

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At ASAPP, our mission is simple: deliver the best AI-powered customer experience—faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. ASAPP’s AI Engineering team is seeking an enterprising, talented and curious machine learning engineer.  We are seeking a highly experienced Lead AI/ML Engineer to join our Core GenerativeAgent team. You will play a pivotal role in designing, building, and deploying cutting-edge AI systems that power mission-critical enterprise applications. This role is ideal for an individual who thrives in ambiguity, is deeply technical, and has a strong product sense paired with deep expertise in foundational models and enterprise AI systems. You will lead the design and delivery of end-to-end voice AI solutions, combining large language models with speech technologies such as speech-to-text, text-to-speech, and real-time streaming audio pipelines. This role requires a hands-on technical leader who can architect low-latency, highly reliable conversational voice systems and guide a team through ambiguity toward production excellence. We are looking for someone who understands the unique constraints of voice experiences, latency, turn-taking, interruption handling, streaming inference, and audio quality, and can translate these into scalable, enterprise-grade systems. This is a hybrid role with weekly in-person responsibilities. We have offices in New York City and Mountain View, CAWhat you'll doLead the design and implementation of scalable ML/AI systems, with a focus on large language models, vector databases, and retrieval-based architecturesIntegrate and apply foundation models from major providers (OpenAI, AWS Bedrock, Anthropic, etc.) for prototyping and production use casesAdapt, evaluate, and optimize LLMs for domain-specific enterprise applicationsBuild and maintain infrastructure for experimentation, deployment, and monitoring of AI models in productionImprove model performance and inference workflows with attention to latency, cost, and reliabilityProvide technical leadership within the team, mentoring engineers and promoting best practices in ML engineeringPartner with product and cross-functional stakeholders to translate requirements into scalable ML solutionsContribute to the evolution of internal standards for experimentation, evaluation, and deploymentWhat you'll need6+ years of experience in Machine Learning or AI systems, with hands-on experience in LLMs, speech, or conversational AI systemsProficiency on Python and ML frameworks like PyTorch or TensorFlowProven experience leading complex, cross-functional AI initiativesExperience building or integrating speech-to-text and text-to-speech systemsDeep understanding of latency-sensitive system design and distributed architecturesStrong proficiency in Python and ML frameworks such as PyTorch or TensorFlowStrong experience integrating foundational models into production applicationsUnderstanding of RAG pipelines, prompt engineering, and vector searchExperience deploying and scaling AI systems using AWS (required), Docker, Kubernetes, and CI/CD practicesStrong communication skills with the ability to align engineering, product, and executive stakeholdersComfortable operating in fast-paced environments and driving clarity in ambiguous problem spacesWhat we'd like to seeExperience with speech model fine-tuning or acoustic/language model optimizationHands-on experience with real-time or streaming audio systems (WebRTC, gRPC streaming, or similar architectures)Experience optimizing TTS prosody, pronunciation control, and voice customizationBackground in MLOps, experimentation platforms, or evaluation frameworks for speech and conversational systemsContributions to open-source AI or speech toolingGraduate degree (MS or PhD) in Computer Science, Machine Learning, Speech Processing, or related field 170,000 - 190,000 a yearCompensation package also includes a performance bonus on top of the listed salary range Separately, we also offer a compelling equity grant comprised of stock optionsBenefits include: Competitive compensation with stock optionsComprehensive medical, vision, and dental insurance 401k matchingFitness and wellness stipendMental well-being benefitsProfessional learning and development stipendParental leave, including adoptive and foster parents3 weeks paid time off (increases with tenure) along with sick leave, bereavement and jury duty ASAPP is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status. If you have a disability and need assistance with our employment application process, please email us at careers@asapp.com to obtain assistance. #LI-AG1 #LI-Hybrid

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About FluidstackAt Fluidstack, we’re building the infrastructure for abundant intelligence. We partner with top AI labs, governments, and enterprises - including Mistral, Poolside, Black Forest Labs, Meta, and more - to unlock compute at the speed of light.We’re working with urgency to make AGI a reality. As such, our team is highly motivated and committed to delivering world-class infrastructure. We treat our customers’ outcomes as our own, taking pride in the systems we build and the trust we earn. If you’re motivated by purpose, obsessed with excellence, and ready to work very hard to accelerate the future of intelligence, join us in building what's next.About the RoleInference is now the defining cost and latency bottleneck for frontier AI. Fluidstack’s Inference Platform team owns the serving layer that sits between our global accelerator supply and the production workloads our customers run on it: LLM serving frameworks, KV cache infrastructure, disaggregated prefill/decode pipelines, and Kubernetes-based orchestration across multi-datacenter footprints.This is a hands-on IC role at the intersection of distributed systems, model optimization, and serving infrastructure. You’ll own end-to-end inference deployments for frontier AI labs and our inference product, drive measurable improvements in throughput, cost-per-token, and time-to-first-token, and contribute to the platform architecture choices that determine how Fluidstack deploys across tens of thousands of accelerators. You will:Own inference deployments end-to-end: from initial configuration and performance tuning to production SLA maintenance and incident response.Drive measurable improvements in throughput, TTFT, and cost-per-token across diverse model families (dense transformers, mixture-of-experts, multi-modal) and customer workload patterns.Build and operate KV cache and scheduling infrastructure to maximize utilization across concurrent requests.Implement and validate disaggregated prefill/decode pipelines and the Kubernetes orchestration that supports them at scale.Profile and resolve bottlenecks at the compute, memory, and communication layers; instrument deployments for end-to-end observability.Partner with customers to translate their model architectures, access patterns, and latency requirements into deployment configurations and upstream platform improvements.Contribute to inference platform architecture and roadmap, with a focus on reducing deployment complexity, improving hardware utilization, and expanding support for new model classes and accelerators.Participate in an on-call rotation (up to one week per month) to maintain the reliability and SLA commitments of production deployments. Basic Qualifications5+ years of professional software engineering experience with a track record of shipping production-quality systems.Strong programming skills in Python and/or Go.Hands-on production experience with at least one LLM serving framework (vLLM, SGLang, TensorRT-LLM, TGI, or equivalent).Working knowledge of PyTorch or JAX and an understanding of how model architecture choices affect inference characteristics.Experience deploying and operating GPU workloads on Kubernetes at production scale, including autoscaling and resource scheduling.Solid understanding of GPU memory hierarchies, compute parallelism, and the tradeoffs across tensor, pipeline, and expert parallelism strategies.Ability to create structure from ambiguity and communicate technical tradeoffs clearly to both engineering peers and customers.Great written and verbal communication skills in English. Preferred QualificationsProduction experience with disaggregated prefill/decode architectures (NVIDIA Dynamo, LLM-d, or equivalent), including scheduling policies and network fabric configuration.Deep familiarity with KV cache strategies: RadixAttention, slab-based memory allocators, cross-request prefix sharing, and cache-aware scheduling.Experience with multi-node GPU inference across InfiniBand or RoCE fabrics, including NCCL collective communication tuning.Custom kernel or operator development experience (e.g., CUDA, Triton, torch.compile, Pallas, or equivalent)Contributions to open-source inference engines (vLLM, SGLang, TGI, TensorRT-LLM, or similar).Hands-on experience with quantization tooling: GPTQ, AWQ, FP8 via llm-compressor, or AutoGPTQ.Knowledge of speculative decoding implementations (Medusa, EAGLE-3, draft-model approaches) and their performance/quality tradeoffs.Experience optimizing and adapting model implementations for non-NVIDIA accelerators and their ecosystems: AMD, TPU, Trainium/Inferentia, Cerebras, Groq, and other custom ASICs. Salary & BenefitsCompetitive total compensation package (salary + equity).Retirement or pension plan, in line with local norms.Health, dental, and vision insurance.Generous PTO policy, in line with local norms. The base salary range for this position is $165,000 – $500,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.We are committed to pay equity and transparency.Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email careers@fluidstack.io with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.

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Who We AreHowdy, we're Heidi 👋"The AI startup growing faster than Canva"That's what the Financial Review called us. In 18 months, we supported over 73 million patient visits and become one of the fastest-growing companies in the world.We pivoted from broad healthcare AI to building Earth's finest AI Care Partner. Today, we support over 2 million patient sessions weekly across 116 countries and over 110 languages. Hundreds of thousands of clinicians use Heidi to complete documentation.Our mission is simple: strengthen the human connection at the heart of healthcare.We've found product-market fit with individual clinicians through our freemium medical scribe, transforming unstructured clinical visits into structured text artefacts. Clinicians and organizations quite like it. Now, we embark upon consuming more than just documentation. Every new job a clinician delegates to Heidi makes patients feel more attended to, cleans up health system logjams, and lets clinicians be clinicians again.That's where you come in.The roleWe're looking for a Product Manager to own the AI models that power everything Heidi does. Someone who thinks platform teams exist to make product teams faster.You will own Heidi's models platform: evaluation pipelines, fine-tuning infrastructure, model routing, and safety systems. Hundreds of thousands of clinicians across 116 countries use these models in clinical settings every week. You'll work with engineers and researchers, partner with product PMs and clinical safety, and stay close enough to product teams that you know what they need before they file a ticket.You will report into Product leadership. This is a platform role. Every user-facing product at Heidi depends on what your team builds.This role will be based in either our Sydney or Melbourne office.We don't care about logos; the traditional insignia of competence. We'll evaluate senior well-credentialed candidates and young, hungry hopefuls alike. If you're an engineer who's been living inside these models and wants to move up a layer of abstraction into product, we want to hear from you.What you'll do:Own product strategy and roadmap for Heidi's models platform (evaluation, safety, model routing, fine-tuning infrastructure), setting clear goals and being held accountable to achieving themPrioritise your team's work across enablement requests, model safety and quality, and bets on new capabilitiesFigure out where product teams get stuck on your models and fix the platform so they don'tBuild eval tooling and fine-tuning workflows that your engineers and product teams can actually use in clinical settingsDecide what to improve next by reading clinician feedback, model quality signals, and what product teams are asking forAllocate engineering capacity across product teams who all want more than you can give, and tell them clearly what you're deferringWork with your engineers on eval design, fine-tuning trade-offs, and model architecture decisions at a technical levelSet model quality and safety targets grounded in clinical outcomes (did the note capture the right diagnosis? did the referral letter contain the right history?)Spot infrastructure that two product teams are building separately and consolidate itWatch foundation model developments and decide when to rip up your roadmapIf we'd worked together the last 6 weeks, you'd have:Defined an evaluation framework for model quality that your engineers actually useMade a clear ship/hold decision on a model update under pressure from a product team, and communicated the rationale to leadershipIdentified overlapping model capability requests across two product teams and proposed shared infrastructureBuilt a 90-day roadmap that balances enablement requests with your own priorities for model qualityHad a productive disagreement with a senior engineer about prioritisation and reached a resolution you both committed toWhat we're looking for:4+ years working on AI platform, infrastructure, or model-adjacent products, though we care more about what you've built than time servedTechnical depth on model evaluation, fine-tuning, and production AI systems. You've designed eval suites, debugged model regressions, and understand what makes models fail in production.Genuine curiosity about what models get wrong in clinical settings and whyTechnical enough to hold your own with your engineers, credible enough to present safety trade-offs to leadershipYou use AI tools to do your own work, not just manage people who doStrong opinions, weakly held. You'll shift the room when you're right.Willingness to update your views when the technology shifts, which it does roughly quarterly.Data fluency with diagnostic teeth - can you read evaluation results and distinguish a real regression from noise? Can you design an eval that catches the thing your current suite misses?If you answer 'NO' to these questions, this may not be the job for you:Are you an execution powerhouse?Have you worked on AI products where model quality directly affected end users?Can you allocate engineering resources across competing priorities and defend the split?Are you comfortable making decisions with incomplete information, then revising them when the picture changes?Are you able to execute without a legion of data analysts, product marketers, and research coordinators at your beck and call?Does the prospect of re-energising our health systems make you feel fuzzy inside?The Way We Work1. Build to LastWe design for safety and reliability so clinicians, patients, and our teams can trust what we build every day.2. Own Your PracticeIdeas rise on merit, not title, and everyone shares responsibility for the standards we set together.3. Move Fast, Stay SteadyWe move quickly but never at the cost of trust. Progress only matters if people can depend on what we make.4. Make Others BetterHonest feedback, steady support, and shared growth keep our teams improving together.Why you will flourish with usFlexible hybrid working environment, with 3 days in the office.A generous personal development budget of $500 per annumLearn from some of the best engineers and creatives, joining a diverse teamBecome an owner, with shares (equity) in the company, if Heidi wins, we all winThe rare chance to create a global impact as you immerse yourself in one of Australia’s leading healthtech startupsIf you have an impact quickly, the opportunity to fast track your startup career!Heidi is dedicated to creating an equitable, inclusive, and supportive work environment that brings people together from diverse backgrounds, experiences, and perspectives. Our strength is in our differences. We're proud to be an equal opportunity employer and welcome all applicants as we're committed to promoting a culture of opportunity for all.

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About the teamOpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development.About the roleForward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams.You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams.This role is based in Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.In this role you willOwn technical delivery across multiple deployments from first prototype to stable productionBuild full-stack systems that deliver customer value and sharpen how we learnEmbed closely with customer teams, understand their needs, and guide adoption of what you buildScope work, sequence delivery, and remove blockers earlyMake trade-offs between scope, speed, and quality; adjust plans to protect deliveryContribute directly in the code when progress or clarity depends on itCodify working patterns into tools, playbooks, or building blocks that others can useShare field feedback that helps Research and Product understand where the models succeed and where they can improveKeep teams moving through clarity and follow-throughYou might thrive in this role if youBring 5+ years of engineering or technical deployment experience that includes customer-facing workHave scoped and delivered complex systems in fast-moving or ambiguous environmentsWrite and review production-grade code across frontend and backend using Python, JavaScript, or comparable stacksHave built or deployed systems powered by LLMs or generative models and understand how model behaviour affects product experienceSimplify complexity and make fast, sound decisions under pressureCommunicate clearly with engineers, product teams, and customer stakeholdersSpot risks early and adjust without slowing downModel calm and judgment when the stakes are highAbout OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About Xaira Therapeutics Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London.Position Overview Xaira is seeking enthusiastic and motivated candidates to join our team as Research Engineers. We welcome candidates across the spectrum of experience. Teams thrive when they are diverse (across all axes), and we encourage all eligible applicants to apply.  The role is based in our London office, located near Old Street. Our team is highly collaborative, operating on the belief that hard problems are best solved by multiple people working towards a clear goal, bringing and sharing their expertise with the team. We operate a hybrid working culture based on trust. Members of the team are typically in the office 3 days a week. Key Responsibilities Industry experience as a research engineer, in an AI-related company. Excited to work, learn and teach within a collaborative team working on challenging problems. Desirable Below is a list of qualities/experiences that align with the kinds of things that we are looking for. Please do not read this as an extension of the “requirements” section! We recognise that experiences, opportunities and life-paths vary. Masters (or equivalent)/PhD in AI-related field. Public codebases or contribution to public GitHub repositories. Experience building and training neural networks. Experience in distributed training and inference. Experience profiling and optimising large-scale AI models. Knowledge or experience in BioAI. If you are a motivated individual with a passion for applying AI to advance drug discovery and improve human health, we encourage you to apply and join us in our mission to make a positive difference in the world. Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end. TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is seeking a ASIC Networking Engineer to help define and build next-generation CPU networking architecture for both datacenter and emerging robotics/automotive applications. You will contribute to our current datacenter networking efforts while also helping to seed and specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingest. The initial focus will be datacenter networking, with robotics as the first target within the automotive/robotics space. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who You Are You thrive while navigating multiple priorities and ambiguous, evolving requirements. You have knowledge of Ethernet  network architecture and how performance is modeled. You have experience with die-to-die interfaces and understand associated protocols and design tradeoffs. You understand Ethernet networking concepts and how they map onto on-chip and off-chip fabrics. You have experience with datacenter scale up architectures like UALink, NVLink, and Broadcom SUE. You have experience with scale out RDMA protocols like RoCE, Infiniband, and others. Experience working on safety (diagnostic and fault coverage) with RTL design process.   What We Need A network ASIC designer who can contribute to both datacenter networking and early-stage automotive/robotics scoping and specifications. Someone comfortable working at the intersection of NoC, performance modeling, and RTL design to guide architectural decisions. An engineer who can collaborate across hardware, software, and systems teams to define and refine networking requirements. A contributor who can help drive forward next-generation CPU networking architecture for AI/ML workloads.   What You Will Learn How to build next-generation CPU networking architectures for both high-performance datacenter and constrained robotics/automotive environments. How to help drive forward next-generation robotics-focused CPUs for AI/ML compute with rich sensor ingestion. How to work at the intersection of NoC design, performance modeling, and RTL to close the loop between architecture and implementation. How to take an early-stage concept (automotive/robotics networking) from seeding and specification through to project initiation.   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is seeking a ASIC Networking Engineer to help define and build next-generation CPU networking architecture for both datacenter and emerging robotics/automotive applications. You will contribute to our current datacenter networking efforts while also helping to seed and specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingest. The initial focus will be datacenter networking, with robotics as the first target within the automotive/robotics space. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who You Are You thrive while navigating multiple priorities and ambiguous, evolving requirements. You have knowledge of Ethernet  network architecture and how performance is modeled. You have experience with die-to-die interfaces and understand associated protocols and design tradeoffs. You understand Ethernet networking concepts and how they map onto on-chip and off-chip fabrics. You have experience with datacenter scale up architectures like UALink, NVLink, and Broadcom SUE. You have experience with scale out RDMA protocols like RoCE, Infiniband, and others. Experience working on safety (diagnostic and fault coverage) with RTL design process.   What We Need A network ASIC designer who can contribute to both datacenter networking and early-stage automotive/robotics scoping and specifications. Someone comfortable working at the intersection of NoC, performance modeling, and RTL design to guide architectural decisions. An engineer who can collaborate across hardware, software, and systems teams to define and refine networking requirements. A contributor who can help drive forward next-generation CPU networking architecture for AI/ML workloads.   What You Will Learn How to build next-generation CPU networking architectures for both high-performance datacenter and constrained robotics/automotive environments. How to help drive forward next-generation robotics-focused CPUs for AI/ML compute with rich sensor ingestion. How to work at the intersection of NoC design, performance modeling, and RTL to close the loop between architecture and implementation. How to take an early-stage concept (automotive/robotics networking) from seeding and specification through to project initiation.   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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About the RoleA1 is building a proactive AI system that carries work forward across conversations, tools, and time.You define what we build and why, grounded in what AI systems can actually do in production. You sit at the intersection of user needs, model capability, and system constraints, and are responsible for turning AI potential into real, reliable user value.This is a hands-on role for product leaders who are comfortable making decisions under uncertainty and working closely with engineers on hard technical trade-offs.What You'll be DoingOwn the end-to-end AI product strategy, grounded in technical feasibility and real-world constraints.Translate model capabilities, data limitations, and evaluation results into clear product decisions.Make hard trade-offs across quality, latency, cost, reliability, and user experience.Work daily with ML, backend, and mobile engineers on design, evaluation, and iteration.Define success metrics and feedback loops across offline evaluation, online experiments, and human feedback.Drive execution with clear specifications, risk awareness, and disciplined prioritization.Ensure AI features ship quickly, safely, and reliably into production.Own AI product quality across UX, correctness, and outcomes.What You Will NeedTechnical foundationStrong grounding in computer science fundamentals, including algorithms, data structures, and system design.Solid understanding of ML fundamentals and how modern AI systems behave in production.Comfort reading, reviewing, and discussing technical design documents.AI & ML experienceHands-on exposure to AI-powered products, including LLM-based systems.Experience working with model evaluation, prompt or pipeline iteration, and feedback loops.Strong intuition for model limitations, hallucinations, bias, and drift.Product leadershipSignificant experience owning complex, technical products end-to-end.Proven ability to work closely with senior engineers and ML teams.Strong judgment and decision-making ability in ambiguous, fast-moving environments.Ability to balance ambition with technical and operational reality.Nice to haveExperience shipping AI-heavy consumer products.Background as an engineer or highly technical product manager.Experience defining evaluation metrics for ML systems.Strong intuition for AI UX patterns and failure handling.Prior experience in zero-to-one product environments.How We WorkOur organization is very flat and our team is small, highly motivated, and focused on engineering and product excellence. All members are expected to be hands-on and to contribute directly to the company’s mission.Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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About the RoleA1 is building a proactive AI system that carries work forward across conversations, tools, and time.You define what we build and why, grounded in what AI systems can actually do in production. You sit at the intersection of user needs, model capability, and system constraints, and are responsible for turning AI potential into real, reliable user value.This is a hands-on role for product leaders who are comfortable making decisions under uncertainty and working closely with engineers on hard technical trade-offs.What You'll be DoingOwn the end-to-end AI product strategy, grounded in technical feasibility and real-world constraints.Translate model capabilities, data limitations, and evaluation results into clear product decisions.Make hard trade-offs across quality, latency, cost, reliability, and user experience.Work daily with ML, backend, and mobile engineers on design, evaluation, and iteration.Define success metrics and feedback loops across offline evaluation, online experiments, and human feedback.Drive execution with clear specifications, risk awareness, and disciplined prioritization.Ensure AI features ship quickly, safely, and reliably into production.Own AI product quality across UX, correctness, and outcomes.What You Will NeedTechnical foundationStrong grounding in computer science fundamentals, including algorithms, data structures, and system design.Solid understanding of ML fundamentals and how modern AI systems behave in production.Comfort reading, reviewing, and discussing technical design documents.AI & ML experienceHands-on exposure to AI-powered products, including LLM-based systems.Experience working with model evaluation, prompt or pipeline iteration, and feedback loops.Strong intuition for model limitations, hallucinations, bias, and drift.Product leadershipSignificant experience owning complex, technical products end-to-end.Proven ability to work closely with senior engineers and ML teams.Strong judgment and decision-making ability in ambiguous, fast-moving environments.Ability to balance ambition with technical and operational reality.Nice to haveExperience shipping AI-heavy consumer products.Background as an engineer or highly technical product manager.Experience defining evaluation metrics for ML systems.Strong intuition for AI UX patterns and failure handling.Prior experience in zero-to-one product environments.How We WorkOur organization is very flat and our team is small, highly motivated, and focused on engineering and product excellence. All members are expected to be hands-on and to contribute directly to the company’s mission.Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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About the roleMaincode is training Matilda, the first large language model built and trained from scratch in Australia. Our new compute cluster is live, and we are now scaling the next version.This role sits directly inside that training stack. You will build the pipelines, infrastructure, and tooling that determine how efficiently Matilda trains, how stable long runs are, and how fast new experiments can be executed. Training runs last days or weeks. Small changes propagate through complex systems. The work requires precision and patience.We build AI systems from first principles: designing the architectures, running the infrastructure, shaping the training process, and operating the models ourselves. Matilda is not a research prototype. It is a production system, trained at scale and served for open public access.Maincode operates one of the largest private AI compute environments in Australia, built for a single purpose: training our own models. This is not a role that wraps external APIs or ships user-facing features. You will be working on the systems that train a large language model from scratch.What you would actually doYou will build and maintain the systems that support large scale model training.This includes:Designing and maintaining distributed training pipelines for large language modelsBuilding data ingestion and preprocessing systems for large training datasetsDeveloping tooling for experiment management, checkpointing, and reproducibilityMonitoring and debugging long running training jobs across clustersImproving reliability and observability across the training stackOptimising training throughput across compute, memory, and data pipelinesWorking closely with researchers to translate experimental ideas into training runsDiagnosing failures across infrastructure, training loops, and data pipelinesTraining runs can last days or weeks. Small changes propagate through complex systems.You will spend time inside code, logs, dashboards, and experiment outputs. The goal is simple: make large scale training reliable.The kind of person who does well hereWe are looking for engineers early in their careers who want to understand how large models are actually trained.You may have one or two years of experience building production software. What matters most is curiosity and the willingness to learn how these systems behave under load.People who tend to do well here:Care about how systems behave over long runtimesEnjoy debugging complex distributed systemsPay attention to logs, metrics, and system behaviourPrefer understanding how a system works rather than relying on abstractionAre comfortable working close to infrastructureHave the patience to diagnose failures that appear hours into a runWant to learn how large scale AI training actually happensYou do not need prior experience training large language models. What matters is intellectual curiosity, persistence, and the ability to learn quickly.How you would workYou will write production code that sits directly in the training stack.You should be comfortable:Working in PythonUsing machine learning frameworks such as PyTorch or JAXWriting reliable infrastructure for large compute workloadsDebugging distributed systems and long running jobsCollaborating closely with researchers and infrastructure engineersMuch of the work sits between research and infrastructure. Ideas move quickly, but the systems that support them must remain stable.What this role is notIt is not primarily about building user facing applicationsIt is not about prompt engineeringIt is not about wrapping external APIs or third party modelsYou will be working on the systems that train our own models from scratch.Why MaincodeMaincode builds AI systems end to end. We prepare the data, design the training process, run the infrastructure, and operate the models ourselves.You will work with a small team that:Builds the full AI stack rather than outsourcing itTreats infrastructure as part of the intelligence system itselfValues engineers who want to understand how things actually workIs building long term capability in training and operating large modelsIf you want to work directly on the systems that train large language models from scratch, this is the only role in Australia that will put you inside that work.NoteThis is a full time role based in Melbourne, working closely with our in person engineering and research team. At this time we are not able to offer visa sponsorship, so applicants must have existing and unrestricted work rights in Australia.

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About the roleMaincode builds foundation models from first principles on Australian infrastructure. We design architectures, run our own compute, shape the training process, and operate the systems that serve our models.We have built Matilda, the first large language model built and trained from scratch in Australia. Our new compute cluster is live; we are scaling the next version of Matilda and deploying and serving it live for public access.We are looking for AI researchers who want to work on the core architecture, training, and evaluation of large-scale language models that power Matilda.This role is not focused on incremental benchmarking or paper output. You will work directly with the engineers running large-scale training systems and help design models that learn efficiently and behave reliably in production.What you would actually doYou will work across the model development loop, from research questions to training runs to evaluation.This includes:Designing and testing architecture changes and training regimes for large language modelsRunning controlled experiments at scale and isolating causal effectsStudying failure modes in reasoning, generalisation, robustness, and representationShaping objectives, data mixtures, and optimisation choices that influence model behaviourBuilding and refining evaluations that measure capability and reliability, not just scoresAnalysing training dynamics using logs, metrics, and model outputsCollaborating with ML systems engineers on distributed training and training operationsWriting clear internal notes that turn experimental results into design decisionsYou will spend substantial time in code, training runs, logs, and evaluation outputs. The goal is clarity about what improves the model and why.What we are looking forWe care about depth of reasoning, experimental discipline, and the ability to make progress under ambiguity.We expect:Hands-on experience writing and running production-grade ML or research codeStrong Python and experience with PyTorch or JAXSolid understanding of transformer-based language models and the basics of pre-training and evaluationAbility to design experiments, interpret results, and communicate tradeoffs clearlyComfort working close to infrastructure, performance constraints, and operational realityInterest and exposure to reasoning-oriented architectures and training methods beyond standard approaches, and beyond standard LLMs Nice to haveExperience with distributed training concepts and tooling (data parallel, tensor parallel, sharding, checkpointing)Experience running training across multiple nodes and managing long training cyclesFamiliarity with large-model training stacks and frameworks (for example Megatron-style systems, DeepSpeed-like tooling, or equivalent)Comfort across the full workflow: training, evaluation, and deployment constraintsExperience working in ROCm-based environmentsHow you would workThis is hands-on research. You will use code as a primary tool for thinking.You will be expected to:Move between theory and implementation quickly and preciselyPrefer controlled experiments over broad sweepsUse logs, metrics, and model behaviour to guide decisionsWork closely with engineering counterparts to scale and validate ideasWhat this role is notIt is not a product research roleIt is not prompt engineeringIt is not fine-tuning someone else’s model and shipping wrappers around external APIsYou will work on Matilda, trained from scratch on our infrastructure, and pushed until its behaviour is understood and improved.Why MaincodeMaincode builds and operates the full stack: training infrastructure, model code, evaluation systems, and deployment. We run one of the largest private AI compute environments in Australia, built for the sole purpose of training and deploying large scale models.If you want to work directly on training and evaluating a large language model built from scratch, this is the only role in Australia that will put you inside that work.NoteThis is a full time role based in Melbourne, working closely with our in person team. At this time we are not able to offer visa sponsorship, so applicants must have existing and unrestricted work rights in Australia.

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Our Mission:At Sunrise Robotics, we are dedicated to augmenting humanity through intelligent robotics. Our mission is to elevate the world of manufacturing by introducing intelligent, flexible robots that enhance human capabilities and existing machinery, ushering in the next era of production at higher quality, with less waste, and lower cost. Our Vision:We see a future where every element of manufacturing, from design to assembly, is optimised with intelligent automation. Our vision is to integrate flexible robotic solutions, based on generic hardware and advanced software/AI capabilities, into manufacturing, particularly in small and medium-sized enterprises, to make automation economically viable and accessible, for all sizes of manufacturers. We are not just building robots; we are creating the strategically crucial components for autonomous, intelligent agents of the future.The role:Sunrise Robotics is building a new category of intelligent, flexible robotic automation - designed to scale across factories, not just solve one-off integrations. As a Forward Deploy Engineer, you’ll be at the front lines of that transformation.This is a unique role that sits between product and deployment. You’ll work directly with customers to deliver automation solutions in real production environments, while continuously improving how those solutions are packaged, standardised, and scaled. The challenge is not simply delivering systems - it’s helping turn delivery into a repeatable, efficient, productised capability.You’ll bring practical experience from traditional automation or system integration and apply it to a new model: scalable deployment powered by Sunrise tools, products, and processes. Your work will directly shape how we refine our offering for customers and our roadmap for product teams to reduce non-recurring engineering effort and speed market adoption.What you’ll do:Deploy Sunrise robotic systems in live manufacturing environments, ensuring successful customer go-livesTranslate real-world production constraints into structured feedback that improves product capabilities and deployment workflowsIdentify opportunities to reduce non-recurring engineering effort and improve delivery scalabilityContribute to the refinement of Sunrise’s tools, processes, and system architecture to enable repeatable deploymentsCollaborate closely with AI, robotics, product, and commercial teams to align customer needs with product evolutionSupport pilot launches and early deployments, ensuring systems meet defined performance and operational success criteriaAct as a technical partner to customers during integration, building trust and ensuring long-term successProvide technical support to customers during troubleshooting and maintenance of deployed robotic systemsInvestigate and respond to operational incidents or anomalies in robotic systems, ensuring timely resolution and system reliabilityWhat you’ll need:A genuine drive to reinvent how flexible automation solutions are delivered and scaled across manufacturing environmentsHands-on experience deploying robotic systems and automated machinery in real-world industrial settingsStrong understanding of robotics fundamentals and familiarity with deep learning models, including how they can be adapted or re-trained for specific applicationsWorking knowledge of synthetic data generation concepts, simulation environments such as NVIDIA Isaac Sim / Omniverse, and structured quality assurance processesExperience with ROS 2 and Behaviour Tree programming for robotic system controlAn abstract, systems-level thinker who can view problems from multiple perspectives and generalise solutions across different applicationsAbility to collaborate effectively with multidisciplinary teams across AI, mechanical, electrical, and software engineeringStrong communication skills, able to explain complex technical concepts clearly to both technical and non-technical stakeholdersA deep passion for robotics, automation, and building intelligent systems that transform manufacturingWhat Makes You Stand Out:Experience in collaborative applications.Experience with ABB SafeMove.Experience with TIA portal.Experience with radar-based safety.Experience with safety analysis tools.Why Us?We’re building a new category of intelligent, flexible robotic automation with real deployments, real customers, and momentum across Europe.Why this role: You’ll operate at the intersection of product and deployment, helping transform automation delivery from bespoke integration to scalable, repeatable systems.Career acceleration: High ownership, deep cross-functional exposure, and the opportunity to shape how a category-defining robotics company scales globally.Real impact: Your work won’t stay in simulation or design reviews - it will run on real factory floors, directly influencing product evolution, customer success, and company trajectory.

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!About North:North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications.Why This Role?This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. We are seeking engineers with diverse skill sets, including backend, infrastructure, agent development, and deployments, who deeply care about customers and want to work at the cutting edge of Agentic AI.Note: between 20 - 40% travel anticipatedIn this role, you will:Build and ship features for North, our AI workspace platformDevelop autonomous agents that talk to sensitive enterprise dataExperiment at a high velocity and with a high level of quality to engage our customers and ultimately deliver solutions that exceed their expectationsWork across the entire product lifecycle from conceptualization through productionLead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rolloutYou may be a good fit if:You have experience with and enjoy working directly with customersYou are fluent in both English and ArabicYou have shipped (lots of) Python in productionYou have built and deployed highly performant client-side or server-side RAG/agentic applicationsYou have strong coding abilities and are comfortable working across the stack. You’re able to read and understand, and even fix issues outside of the main code baseYou excel in fast-paced environments and can execute while priorities and objectives are a moving targetWe are open to candidates currently based in the Middle East or who are open to travelling or relocating.If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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About AbridgeAbridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. The RoleWe are looking for passionate GenAI Engineers of all levels who are passionate about making a positive impact. You’ll collaborate closely with a cross-functional team of researchers, clinicians, and engineers to translate cutting-edge language model capabilities into dependable, real-world clinical systems. Your focus will be on designing advanced LLM-driven workflows that can reason through complex clinical contexts, leverage agentic capabilities and structured tool use, navigate branching chains of LLM calls, integrate seamlessly with retrieval systems, and consistently generate outputs that meet the highest standards of clinical reliability and trust.A major part of this role will involve developing and applying rigorous evaluation frameworks (both automated and human-in-the-loop) to continuously assess accuracy, robustness, multilingual capabilities, and more. This is an opportunity to design experiments to probe failure modes, simulate edge cases, and stress-test LLM workflows under realistic load and challenging real-world conditions. You’ll apply a disciplined, data-driven approach to understanding model behavior—developing tools to measure system performance, conduct A/B tests against established baselines, and generate clear, actionable insights that inform deployment decisions. This high impact role will own the end-to-end productionization of LLM workflows: deploying models into low-latency, high-uptime environments, building monitoring and observability systems, implementing post-processing guardrails, and managing workflow versioning.What You’ll DoDesign and build GenAI systems that turn LLMs into composable, dependable tools—leveraging retrieval, tool use, agentic reasoning, and structured outputs.Collaborate with ML and infra engineers to scale and optimize GenAI workflows, managing latency, context windows, and model choice.Write high-quality, modular code that’s graceful under failure, flexible to change, and easy to iterate on.Own major architectural decisions—how we architect workflows,define data flow, cache intermediate state, and structure generative outputs.Drive rigorous evaluation: build benchmark datasets, develop automated and human-in-the-loop frameworks, design experiments to surface failure modes and edge cases, run A/B tests to inform deployment, and distill insights from clinician feedback to evaluate and guide model improvement.Leverage frontier capabilities: rapidly prototype with new models and model capabilities, open-source tools, and novel prompting techniques.What You’ll Bring3+ years of experience building production-grade systems, with 1–2+ years focused on GenAI or LLM-powered products.Deep fluency with LLM APIs, prompting strategies, and orchestration patterns (e.g., LangChain, LlamaIndex, custom pipelines).Experience with retrieval systems (e.g., semantic and lexical retrieval, vector DBs, efficient kNN), function calling, tool-use, or agentic workflows.Working knowledge of model evaluation, experience building diverse datasets, conducting both automated and human-in-the-loop evaluations, running A/B tests, and working with subject matter experts to guide model improvement.Strong Python fundamentals—including ability to write clean code, design comprehensive test-cases, and familiarity with core language features and standard libraries; experience with async programming, performance profiling, packaging, and deployment tooling is strongly preferred.Good taste and intuition: You know when to move fast, ship, and iterate and also when to take a beat to tackle tech debt.We value people who are eager to learn new things and recognize that great team members might not perfectly match a job description. If you’re interested in the role but aren’t sure whether or not you’re a good fit, we’d still like to hear from you.Must be willing to work from our SF office at least 3x per weekThis position requires a commitment to a hybrid work model, with the expectation of coming into the office a minimum of (3) three times per week. Relocation assistance is available for candidates willing to move to San Francisco.Why Work at Abridge?At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month.Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business.Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients.We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life.If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you. How we take care of Abridgers:Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employeesComprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families.Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA.Paid Parental Leave: Generous paid parental leave for all full-time employees.Family Forming Benefits: Resources and financial support to help you build your family.401(k) Matching: Contribution matching to help invest in your future.Personal Device Allowance: Tax free funds for personal device usage.Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more.Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals.Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment.Compensation and Equity: Competitive compensation and equity grants for full time employees.... and much more!Equal Opportunity EmployerAbridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.Staying safe - Protect yourself from recruitment fraudWe are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article. Please exercise caution and cease communications if something feels suspicious about your interactions. 

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About the roleWe are looking for a Partner AI Deployment Engineer (P-ADE) to lead technical delivery with OpenAI partners across EMEA and help scale customer deployments built on the OpenAI platform. This role focuses on working across a wide range of customer use cases, supporting the design, deployment and scaling of production-grade AI solutions delivered through partners.You will work closely with partner delivery teams, alongside Solutions Engineers (SEs), Forward Deployed Engineers (FDEs) and other ADEs, to move customer engagements from initial design through to stable, scaled production. Your work will accelerate time to value, reduce delivery risk and ensure solutions meet OpenAI’s standards for quality, safety and reliability. You will collaborate closely with GTM, Applied, and Research to support partner-led enterprise adoption.This role is based in Paris or Munich. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.In this role, you will:Act as a primary technical delivery partner for a set of OpenAI partners across EMEA, supporting customer deployments across multiple industries and use cases.Work with partner delivery teams and customer stakeholders to translate solution designs into deployable, production-ready architectures on the OpenAI platform.Support customer time to value through hands-on prototyping, integration support, architectural guidance and troubleshooting during critical phases of delivery.Collaborate closely with SEs, FDEs, and other ADEs to ensure the right technical expertise is engaged from design through production rollout.Help partners operationalise solutions by addressing scalability, reliability, security and safety considerations required for enterprise production environments.Contribute to reusable deployment patterns, reference architectures and delivery guidance that enable repeatable execution across partner engagements.Act as a technical quality and governance point during deployments, helping ensure solutions meet OpenAI’s standards and best practices before and after go-live.Capture and synthesise feedback from real customer deployments and share insights with Applied, Research and partner teams to improve delivery playbooks and platform capabilities.You’ll thrive in this role if you:Have 8+ years of experience in technical consulting, solution delivery or a similar role, working with senior technical and business leaders on complex enterprise deployments.Have experience delivering large, multi-stakeholder technical projects in partnership with boutique services organisations, system integrators or similar delivery environments.Have strong hands-on experience building, integrating and operating production software using modern languages such as Python or JavaScript.Have designed, deployed and supported Generative AI and or machine learning solutions in real-world production environments.Have practical experience working with the OpenAI platform in customer-facing or delivery contexts.Are a clear communicator who can work effectively with partner engineers, internal teams and customer stakeholders.Take ownership of delivery problems end to end and are comfortable operating in ambiguous, fast-moving environments.Bring a collaborative, humble mindset and enjoy working across partners and internal teams to deliver successful customer outcomes.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.