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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $58 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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Company OverviewDeepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.Company Operating RhythmAt Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance.Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.The OpportunityVoice is the most natural modality for human interaction with machines. However, current sequence modeling paradigms based on jointly scaling model and data cannot deliver voice AI capable of universal human interaction. The challenges are rooted in fundamental data problems posed by audio: real-world audio data is scarce and enormously diverse, spanning a vast space of voices, speaking styles, and acoustic conditions. Even if billions of hours of audio were accessible, its inherent high dimensionality creates computational and storage costs that make training and deployment prohibitively expensive at world scale. We believe that entirely new paradigms for audio AI are needed to overcome these challenges and make voice interaction accessible to everyone.The RoleDeepgram is seeking a highly skilled and versatile Machine Learning Engineer to join our Research team. As a Member of the Research Staff, you will partner with research scientists to prototype and validate novel modeling ideas, then scale them through robust training systems for speech technologies, internal tooling, and innovative data strategies. You'll work at the intersection of machine learning, data infrastructure, and internal tooling to support our mission of building world-class speech recognition and synthesis systems. On the Research team, you will experiment with new technologies and techniques, while also working on product-focused deliverables, learning from colleagues with a wide range of expertise in AI and machine learning as you go. Key ResponsibilitiesScalable Model Training: Architect and manage horizontally scalable systems that dramatically accelerate the end-to-end training lifecycle for Speech-to-Text (STT) and Text-to-Speech (TTS) models. This includes far more than automated training: the role focuses on making model development significantly faster and more efficient through optimized data preparation and management, high-throughput training pipelines, distributed infrastructure, and automated evaluation tooling. Tooling & Accessibility: Design and implement internal UIs and tools that make ML systems and workflows accessible to non-technical stakeholders across the company. These UIs should be designed to provide transparency and flexibility to internally built tooling.Infrastructure & Tools: Oversee and manage training tooling, job orchestration, experiment tracking, and data storage. The ChallengeWe are seeking Members of the Research Staff who:See "unsolved" problems as opportunities to pioneer entirely new approachesCan identify the one critical experiment that will validate or kill an idea in days, not monthsHave the vision to scale successful proofs-of-concept 100xAre obsessed with using AI to automate and amplify your own impactIf you find yourself energized rather than daunted by these expectations—if you're already thinking about five ideas to try while reading this—you might be the researcher we need. This role demands obsession with the problems, creativity in approach, and relentless drive toward elegant, scalable solutions. The technical challenges are immense, but the potential impact is transformative.It's Important to Us That You HaveStrong experience with the machine learning research pipeline, particularly in STT or related speech domains. This includes experimenting with and evaluating new architectures and modeling approaches, and implementing large-scale training systems.Proficiency with orchestration and infrastructure tools like Kubernetes, Docker, and Prefect.Familiarity with ML lifecycle tools such as MLflow.Experience building internal tools or dashboards for non-technical users.Hands-on experience with data engineering practices for unstructured audio and text data.Comfortable working in cross-functional teams that include researchers, engineers, and product stakeholders. Why Join Deepgram?At Deepgram, you’ll help shape the future of human–machine communication. Our research culture prioritizes ownership, experimentation, and real-world impact. As a Member of the Research Staff, you'll be empowered to build tools and systems that accelerate ML research and product deployment at scale.Benefits & Perks*Holistic healthMedical, dental, vision benefitsAnnual wellness stipendMental health supportLife, STD, LTD Income Insurance PlansWork/life blendUnlimited PTOGenerous paid parental leaveFlexible schedule12 Paid US company holidaysQuarterly personal productivity stipendOne-time stipend for home office upgrades401(k) plan with company matchTax Savings ProgramsContinuous learningLearning / Education stipendParticipation in talks and conferencesEmployee Resource GroupsAI enablement workshops / sessions*For candidates outside of the US, we use an Employer of Record model in many countries, which means benefits are administered locally and governed by country-specific regulations. Because of this, benefits will differ by region — in some cases international employees receive benefits US employees do not, and vice versa. As we scale, we will continue to evaluate where we can create more alignment, but a 1:1 global benefits structure is not always legally or operationally possible.Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $215M in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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RYZ Labs is looking for an experienced AI Evaluation Engineer to join one of our clients’ teams. Responsibilities Design and implement evaluation pipelines to measure the performance and reliability of AI models. Develop automated testing frameworks to assess model outputs at scale. Analyze model performance using both traditional statistical metrics and AI-specific evaluation methods. Evaluate AI systems built on modern architectures such as LLM-based applications and Retrieval-Augmented Generation (RAG). Identify potential issues related to accuracy, hallucinations, bias, safety, and model drift. Conduct adversarial testing to uncover vulnerabilities and ensure safe model behavior. Collaborate with engineering and AI teams to improve prompt design, model outputs, and system performance. Monitor model performance in production and help define best practices for AI evaluation and observability. Requirements Proficiency in Python and experience building scripts or pipelines to evaluate model outputs. Experience working with AI/ML systems, particularly large language models (LLMs) or generative AI applications. Familiarity with concepts such as prompt engineering, prompt optimization, and LLM evaluation. Understanding of evaluation metrics such as precision, recall, F1-score, and AI-specific metrics related to model quality and safety. Experience evaluating RAG systems or knowledge retrieval pipelines is a plus. Experience with modern AI evaluation or observability tools is a plus (e.g., DeepEval, Promptfoo, RAGAS, LangSmith, Arize, Weights & Biases). Strong analytical mindset with the ability to interpret model behavior and propose improvements. Nice to Have Experience performing adversarial testing or red-teaming of AI systems. Familiarity with AI safety, bias detection, and model alignment practices. Experience working in production environments deploying or monitoring AI systems. About RYZ Labs:   RYZ Labs is a startup studio founded in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together was their passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world.   Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge cloud computing technologies to create scalable and resilient applications. We aim to provide diverse product solutions for different industries and plan to build a large number of startups in the upcoming years.   At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion, and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists.   Our values and what to expect:   - Customer First Mentality - Every decision we make should be made through the lens of the customer. - Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated. - Ownership - Step up if you see an opportunity to help, even if it's not your core responsibility.  - Humility and Respect - Be willing to learn, be vulnerable, and treat everyone who interacts with RYZ with respect. - Frugality - being frugal and cost-conscious helps us do more with less - Deliver Impact - get things done most efficiently.  - Raise our Standards - always be looking to improve our processes, our team, and our expectations. The status quo is not good enough and never should be.    

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design rigorous statistics problems reflecting professional practice; Evaluate AI solutions for correctness, assumptions, and constraints; Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); Improve AI reasoning to align with industry-standard logic; Apply structured scoring criteria to multi-step problems.What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. 3+ years of professional mathematics experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $73 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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About the RoleThe mission of Neural Concept’s Application Engineering team is to help our customers solve their most complex engineering challenges. We collaborate closely with engineering and design teams within the automotive, aerospace and energy industries, understand their challenges and pains, and help them identify solutions to accelerate their conception processes. We leverage our platform to unlock the value of the most complex computer-aided engineering datasets and to create a direct impact on product design processes. Using 3D deep learning and engineering intelligence, we empower our customers to develop better products faster.As a key player in the Application Engineering Team, your mission will be to help industry leaders to redefine their product design workflow with cutting-edge technologies. Your expertise should establish trust and admiration from our customers by delivering high-quality technical work. This is a chance to be at the intersection of engineering and AI, working with top-tier customers worldwide while shaping how the industry evolves. If you are interested in feeling firsthand the fast progress of engineering, this is the team for you.What you will do You will run projects together with our customer’s engineering teams, analyze and process engineering data using our platform and python libraries, and develop tailored solutions and workflowsYou will apply our machine- and deep-learning workflows to different engineering/physics problems, as well as deliver proofs-of-concept demonstrating how our technology creates value in CAD, CAE, and manufacturing. You will train customer teams to effectively use our methods and platform, ensuring smooth AI adoption into their workflows.You will work closely with our developers to translate customer needs and feedback into product improvements.Who you are You are eager to tackle real-world challenges through machine learning and automation, with a passion for reshaping how engineering is practiced by industry leadersYou hold a Master’s or PhD degree in Engineering, Applied Mathematics, or Physics You have an excellent understanding of both Engineering and Machine Learning (strict requirement)You have strong experience with Python programming, and experience with machine learning and deep learning frameworks and libraries (strict requirement)You have experience with simulation. Industry experience in CAD / CAE (CFD, FEM, etc) modelling is a plus You can convey technical concepts to both technical and non-technical stakeholders in a clear and compelling way You have excellent communication skills, enjoy working with people, and feel comfortable in the customer-facing roleYou are fluent in English (mandatory)What You GetWork with a world-class technology team – our engineers are top-notch, and we always aim for excellence.Benefit from a competitive salary and rewarding opportunities as we continue to scale.Thrive in a collaborative, multicultural environment where your work is visible and recognized.Develop professionally alongside talented colleagues who share knowledge freely and support one another.Make a global impact by helping customers shift to AI-assisted design, making innovation faster, smarter, and more sustainable.Balance life and work with a hybrid model and flexible hours—we care about results, not rigid schedules.We're proud to be an equal opportunity employer, and we're committed to building a diverse and inclusive environment where you can thrive.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design rigorous statistics problems reflecting professional practice; Evaluate AI solutions for correctness, assumptions, and constraints; Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); Improve AI reasoning to align with industry-standard logic; Apply structured scoring criteria to multi-step problems.What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. 3+ years of professional mathematics experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $34 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $58 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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About the RoleWe're looking for a Solutions Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems.This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains.This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture.About Us:At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Key ResponsibilitiesInfrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelinesAgent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operationsCustomer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teamsWhat We're Looking For Required Experience7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to applyInfrastructure & Platform:3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure)Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deploymentsExperience with Infrastructure as Code (Terraform, Helm) and GitOps practicesKnowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizingExperience designing high-availability and disaster recovery solutionsStrong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog)Experience with CI/CD pipelines for infrastructure and applicationsAgent Engineering & Development:1+ years of experience building production AI/ML applications or agentsStrong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applicationsExperience with state management patterns (short-term and long-term memory)Experience designing and implementing evaluation frameworks for AI applicationsStrong prompt engineering skills with experience in optimization and A/B testingExperience with vector stores, RAG patterns, and knowledge organizationExperience with tool integration, API design, and error handling patternsStrong Python and/or TypeScript development skillsCustomer-Facing:Customer-facing experience with enterprise customersExperience conducting technical assessments or infrastructure auditsStrong communication skills with ability to explain technical concepts to diverse audiencesKey AttributesStrong problem-solving skills with ability to analyze complex requirements and design elegant solutionsExcellent customer-facing communication skills, able to explain technical concepts to diverse audiencesExperience working cross-functionally with engineering teams, product teams, and customersConsultative approach with ability to understand customer needs, provide recommendations, and guide implementationAbility to balance infrastructure architecture with agent development workStrong engineering background with hands-on development experienceLocation: New York CityCompensation: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.$170K to $190K

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About the RoleWe're looking for a Solutions Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems.This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains.This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture.About Us:At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Key ResponsibilitiesInfrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelinesAgent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operationsCustomer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teamsWhat We're Looking For Required Experience7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to applyInfrastructure & Platform:3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure)Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deploymentsExperience with Infrastructure as Code (Terraform, Helm) and GitOps practicesKnowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizingExperience designing high-availability and disaster recovery solutionsStrong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog)Experience with CI/CD pipelines for infrastructure and applicationsAgent Engineering & Development:1+ years of experience building production AI/ML applications or agentsStrong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applicationsExperience with state management patterns (short-term and long-term memory)Experience designing and implementing evaluation frameworks for AI applicationsStrong prompt engineering skills with experience in optimization and A/B testingExperience with vector stores, RAG patterns, and knowledge organizationExperience with tool integration, API design, and error handling patternsStrong Python and/or TypeScript development skillsCustomer-Facing:Customer-facing experience with enterprise customersExperience conducting technical assessments or infrastructure auditsStrong communication skills with ability to explain technical concepts to diverse audiencesKey AttributesStrong problem-solving skills with ability to analyze complex requirements and design elegant solutionsExcellent customer-facing communication skills, able to explain technical concepts to diverse audiencesExperience working cross-functionally with engineering teams, product teams, and customersConsultative approach with ability to understand customer needs, provide recommendations, and guide implementationAbility to balance infrastructure architecture with agent development workStrong engineering background with hands-on development experienceLocation: Dallas, TXCompensation: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.$170K to $190K

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $34 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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About the TeamThe Future of Computing Research team is an applied research team in the Consumer Devices group focused on developing new methods and models to support our vision as we advance forward in our mission of building AGI that benefits all of humanity. About the RoleAs a Technical Lead on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities.This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees.In this role, you will:Evaluate and select silicon platforms (GPUs, NPUs, and specialized accelerators) for on-device and edge deployment of OpenAI models.Work closely with research teams to co-design model architectures that meet real-world deployment constraints such as latency, memory, power, and bandwidth.Analyze and model system performance, identifying tradeoffs between model design, memory hierarchy, compute throughput, and hardware capabilities.Partner with hardware vendors and internal infrastructure teams to bring up new accelerators and ensure efficient execution of transformer workloads.Build and lead a team of engineers responsible for implementing the low-level inference stack, including kernel development and runtime systems.Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of.You might thrive in this role if you:Have experience evaluating or deploying workloads on GPUs, NPUs, or other specialized accelerators.Understand the performance characteristics of transformer models, including attention, KV-cache behavior, and memory bandwidth requirements.Have designed or optimized high-performance compute systems, such as inference engines, distributed runtimes, or hardware-aware ML pipelines.Have experience building or leading teams working on low-level performance-critical software such as CUDA kernels, compilers, or ML runtimes.Have already spent time in the weeds teaching models to speak and perceive.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.

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About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!About Snorkel We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them - either by leveraging Snorkel Flow or developing custom approaches when needed. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel Flow’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end. Main Responsibilities Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This may involve leveraging Snorkel Flow or designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of the Snorkel platform. Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows. Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role. Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow. Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup. Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices. Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI. Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams. Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI. Annual travel up to 25%. Preferred Qualifications B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience. 3+ years of customer-facing experience in the design and implementation of AI/ML solutions. Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow). Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI). Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement. Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos. Ability to work in a fast-paced environment and balance priorities across multiple projects at once. Compensation range for Tier 1 locations of San Francisco Bay Area $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Locations Redwood City, CA - Hybrid; San Francisco, CA - Hybrid - US; New York, NY - Hybrid #LI-CG1Salary Range $172,000—$300,000 USDBe Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design rigorous statistics problems reflecting professional practice; Evaluate AI solutions for correctness, assumptions, and constraints; Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); Improve AI reasoning to align with industry-standard logic; Apply structured scoring criteria to multi-step problems.What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. 3+ years of professional mathematics experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $50 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design rigorous statistics problems reflecting professional practice; Evaluate AI solutions for correctness, assumptions, and constraints; Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); Improve AI reasoning to align with industry-standard logic; Apply structured scoring criteria to multi-step problems.What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. 3+ years of professional mathematics experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $73 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started.Role OverviewHarvey’s products all depend on a shared AI foundation: the model layer and agent infrastructure that determine the quality of work our agents deliver. Legal is one of the hardest domains for AI: documents run to hundreds of pages, matters can span millions of files, and there is zero margin for error on accuracy.The AI Platform team builds the foundation that every product and agent team at Harvey builds upon. This team is early and there’s a lot to build: model routing, agent architecture, context management, evals. Your work here sets the ceiling for what Harvey’s AI can do.Representative ProjectsContext Engineering & Agent Infrastructure. Build the platform-level systems for context management, session state, and memory that all of Harvey’s agents and products rely on.Model Integration & Routing. Own the infrastructure that lets Harvey onboard new foundation models fast and route to the right one for every task - a capability every product team depends on.Evaluation Infrastructure. Build the shared eval tooling and frameworks that let every team across Harvey measure and improve AI quality systematically.Shared Abstractions. Create the SDKs, platform primitives, and developer tooling that make it dramatically easier for product teams to ship AI-powered features.What You’ll DoDesign and build abstractions and platform-level systems that improve all of Harvey’s agentic products.Own infrastructure for model integration, routing, and evaluation that helps Harvey choose and deploy the right foundation model for any given context.Build evaluation frameworks and tooling that let every team across Harvey iterate on AI quality effectively.Partner closely with product engineering teams, PMs, and design to launch cutting-edge AI products.Evaluate, prototype, and integrate the latest advancements in AI and agentic systems as they emerge.What You Have5+ years of experience building backend systems, with at least 1+ year focused on AI/ML engineering. Staff candidates will typically have 8+ years and a track record of technical leadership across teams.Experience building and shipping multi-model or multi-provider AI systems in production.Familiarity with context management, session state, or memory systems in AI or distributed systems. You’ve thought about what the model sees and why it matters.A track record of building internal platforms, SDKs, or shared infrastructure that other engineering teams actually adopted - and an understanding of why developer experience matters as much as raw capability.Strong judgment about abstractions. Opinionated about good design but pragmatic about shipping incrementally.Excitement about agentic AI and the infrastructure challenges of making autonomous systems reliable when the stakes are real.A bias toward full ownership: you navigate ambiguity well and don’t wait for a roadmap to start solving problems.Bonus: experience building evaluation frameworks, working with agent/function-calling architectures, familiarity with legal or other high-stakes professional services domains, or time at early-stage or hyper-growth startups where the underlying technology changes regularly.Compensation$220,000 - $300,000Please find our CA applicant privacy notice here.Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design rigorous statistics problems reflecting professional practice; Evaluate AI solutions for correctness, assumptions, and constraints; Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); Improve AI reasoning to align with industry-standard logic; Apply structured scoring criteria to multi-step problems.What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. 3+ years of professional mathematics experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $38 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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About the TeamThe Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models to support our vision for the future of computing as we advance forward in our mission of building AGI that benefits all of humanity. About the RoleAs a Research Engineer/Scientist on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities.This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees. In this role you will:Train and evaluate SoTA models along axis that are important to our vision for future devices.Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of.Help define how software works for decades to come.You might thrive in this role if you:Have 5+ years of relevant work experience.Have a research background in utilizing and training language models to generate UI, and developing recipes to evaluate the quality / applicability of UI generated.Love exposure to a bit of everything – we’re collaborators with a hugely diverse set of research.Do rigorous science (rather than vibes based). We need confidence in the experiments we run to move quickly.Have already spent time in the weeds teaching models to speak and perceive.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.

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started.Role OverviewHarvey’s products all depend on a shared AI foundation: the model layer and agent infrastructure that determine the quality of work our agents deliver. Legal is one of the hardest domains for AI: documents run to hundreds of pages, matters can span millions of files, and there is zero margin for error on accuracy.The AI Platform team builds the foundation that every product and agent team at Harvey builds upon. This team is early and there’s a lot to build: model routing, agent architecture, context management, evals. Your work here sets the ceiling for what Harvey’s AI can do.Representative ProjectsContext Engineering & Agent Infrastructure. Build the platform-level systems for context management, session state, and memory that all of Harvey’s agents and products rely on.Model Integration & Routing. Own the infrastructure that lets Harvey onboard new foundation models fast and route to the right one for every task - a capability every product team depends on.Evaluation Infrastructure. Build the shared eval tooling and frameworks that let every team across Harvey measure and improve AI quality systematically.Shared Abstractions. Create the SDKs, platform primitives, and developer tooling that make it dramatically easier for product teams to ship AI-powered features.What You’ll DoDesign and build abstractions and platform-level systems that improve all of Harvey’s agentic products.Own infrastructure for model integration, routing, and evaluation that helps Harvey choose and deploy the right foundation model for any given context.Build evaluation frameworks and tooling that let every team across Harvey iterate on AI quality effectively.Partner closely with product engineering teams, PMs, and design to launch cutting-edge AI products.Evaluate, prototype, and integrate the latest advancements in AI and agentic systems as they emerge.What You Have5+ years of experience building backend systems, with at least 1+ year focused on AI/ML engineering. Staff candidates will typically have 8+ years and a track record of technical leadership across teams.Experience building and shipping multi-model or multi-provider AI systems in production.Familiarity with context management, session state, or memory systems in AI or distributed systems. You’ve thought about what the model sees and why it matters.A track record of building internal platforms, SDKs, or shared infrastructure that other engineering teams actually adopted - and an understanding of why developer experience matters as much as raw capability.Strong judgment about abstractions. Opinionated about good design but pragmatic about shipping incrementally.Excitement about agentic AI and the infrastructure challenges of making autonomous systems reliable when the stakes are real.A bias toward full ownership: you navigate ambiguity well and don’t wait for a roadmap to start solving problems.Bonus: experience building evaluation frameworks, working with agent/function-calling architectures, familiarity with legal or other high-stakes professional services domains, or time at early-stage or hyper-growth startups where the underlying technology changes regularly.Compensation$220,000 - $300,000Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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SUPERHUMAN MAIL 👉 We exist so that professionals end each day feeling happier, more productive, and closer to achieving their potential. Our customers get through their inboxes twice as fast; many see inbox zero for the first time in years. Today we are… The fastest email experience in the world Loved and adored: see what our customers say 📣 We've joined forces with Grammarly to build the AI-native productivity suite of the future, with Superhuman as the central communication layer. This partnership accelerates our mission to help professionals achieve their potential — now at even greater scale. Come shape the future of email, communication, and productivity! BUILD LOVE 💜 At Superhuman, we deeply understand how to build products that people love. We incorporate fun and play; we infuse magic and joy; we make experiences that amaze and delight. It all starts with the right team — a team that deeply cares about values, customers, and each other. CREATE MASSIVE IMPACT 🚀 We're not solving a small problem, and we're not addressing a small market. We're going after email; the one activity that consumes more of our work day than any other. Our ambition doesn't stop there. Next: calendars, notes, contacts, and team communication. We are building the productivity platform of the future. DO THE BEST WORK OF YOUR LIFE 🌟 We have created the frameworks for how to build product market fit and redefined the narrative of how to onboard customers successfully. We have shown the world it’s possible to build a premium productivity brand. Our investors included Andreessen Horowitz, First Round Capital, IVP, Tiger Global Management, Sam Altman, and the founders of Gmail, Dropbox, Reddit, Discord, Stripe, GitHub, AngelList, and Intercom. This time, we’re swinging beyond the fences and fundamentally rethinking how individuals and teams should collaborate. We are building a household brand and a worldwide organization. We are here to do the best work of our lives, and we hope you are too. ROLE 👩🏽‍💻👨‍💻 Own the observability and lifecycle management of AI features across the organization Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features Design and implement closed-loop evaluation pipelines that automatically validate prompt changes Develop comprehensive metrics and dashboards to track LLM usage: cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls Establish best practices and processes for the full lifecycle of prompts: development, testing, deployment, and monitoring Collaborate with engineering teams across the org to ensure they have the tools and visibility needed to build high-quality AI features Technologies we use: Go, Postgres, Kubernetes, Google Cloud, various LLM providers (OpenAI, Anthropic, Google Vertex) SOUND LIKE YOU? 🙌 Experience: You have 4+ years of software development experience with a focus on backend engineering, DevOps, ML Ops, or SRE work. You're proficient in at least one back-end programming language (ideally Go). You have hands-on experience with observability, metrics, and monitoring systems. AI Enthusiast: You believe AI will revolutionize how we work as well as the experiences that we create for our customers. Driven by passion and curiosity, you leverage AI to dramatically increase your own productivity and the impact of your team. Metrics-Driven: You understand percentiles (P90, P95), know how to build meaningful dashboards, and can turn raw data into actionable insights. You've worked with monitoring and observability tools. Systems Thinker: You think in terms of pipelines, lifecycles, and closed loops. You know how to build scalable infrastructure that enables other teams to move faster. Remarkable Quality: You produce work that is striking, worthy of attention, and a contribution to the state of the art. Asynchronous Communicator: You’re effective across various mediums (especially Slack, Notion, and email) and can produce and consume detailed written materials as needed without sacrificing speed. You respond quickly and thoughtfully to unblock others and speed things up. Start-to-Finish Ownership: Acts with 100% responsibility for their own outcomes as well as the outcomes of the company. Bias to action: Speed matters. Takes rapid and decisive steps forward, even in the face of uncertainty, recognizing action is the catalyst for progress and growth. Growth Mindset: You embrace challenges, welcome feedback, and believe you and others can always grow. SALARY INFO 💸 Superhuman takes a market-based approach to compensation, which means base pay may vary depending on your location. Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined below by location and may be modified in the future. Canada: $128,000-$174,000 CAD Mexico: $1,928,000-$2,405,000 MXN Brazil: R$562,000-R$702,000 BRL Argentina: $103,000-$128,000 USD The salary ranges do not reflect total compensation, which includes base salary, benefits, and company equity. This range is intentionally broad because we are open to considering candidates at multiple levels of seniority within engineering. The exact salary offered will depend on the candidate’s skills, experience, and the level at which they join our team. BENEFITS 🎁 Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more: Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits) Disability and life insurance options 401(k) and RRSP matching (US & Canada only) Paid parental leave 20 days of paid time off per year, 12 days of paid holidays per year (17 days for LatAm), two floating holidays per year, and flexible sick time Generous stipends (including those for caregiving, pet care, wellness, your home office, and more) Annual professional development budget and opportunities Superhuman takes a market-based approach to compensation, so base pay may vary by location. COME JOIN US 🎟️ We value our differences, and we encourage all to apply — especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada). #LI-Remote

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About the RoleYou are the engineering backbone of the internal tools team. Building and maintaining the platforms that every team in the company relies on. Your work directly increases organizational efficiency and enables teams to move faster.You’ll own systems end-to-end, from scoping and architecture through production deployment and iteration, connecting multiple business systems into a seamless, reliable internal ecosystem.What You'll DoBuild & ShipDesign, build, and maintain internal platforms and tools that serve People, Finance, Ops, Sales, and Engineering teams.Own features end-to-end: requirements, architecture, implementation, testing, deployment, and monitoring.Write clean, well-tested, production-grade code. You hold yourself to the same bar as customer-facing products.Architecture & IntegrationBuild API-first integrations across the internal ecosystem — connecting HRIS, CRM, finance platforms, knowledge management, and developer tools into a coherent stack.Design for reliability, performance, and scale — what you build today must hold as the company grows 5–10x.Eliminate data silos. Build clean data pipelines that maintain a single source of truth across systems.Own your services in production: monitoring, alerting, incident response, and post-mortems.AI & AutomationBuild AI/LLM-powered features into internal workflows — automating approvals, knowledge retrieval, reporting, content generation, and operational processes.Move fast from prototype to production. You know the difference between a demo and a system that works at scale.Stay current on emerging AI capabilities and proactively identify where they unlock step-change improvements in internal productivity.Collaboration & InfluenceWork directly with business stakeholders to understand pain points and translate them into technical solutions. You don’t wait for a spec — you help shape it.Pair with and mentor junior engineers. Raise the technical bar through code reviews, design reviews, and leading by example.Influence technical direction: propose architectural improvements, challenge assumptions, and drive best practices across the team.What You Will NeedMust-Have5+ years of professional software engineering experience, with meaningful time spent building internal tools, platforms, or business systems.Strong full-stack or backend engineering skills. Proficient in at least one of: Python, Go, TypeScript/Node.js, or Java.Solid understanding of cloud infrastructure (GCP/AWS/Azure), containerisation (Docker/Kubernetes), CI/CD pipelines, and modern DevOps practices.Hands-on experience building and maintaining API integrations between third-party SaaS platforms (e.g., Workday, Salesforce, Slack, NetSuite).Strong data fundamentals: relational databases, data modelling, ETL/ELT pipelines, and working knowledge of SQL.Comfort with ambiguity. You can take a vague business problem, break it down, and deliver a working solution without heavy hand-holding.Clear communicator who can explain technical tradeoffs to non-technical stakeholders.Nice-to-HaveExperience with workflow orchestration tools (Temporal, Airflow, Prefect) or integration platforms (Workato, Tray.io, MuleSoft).Frontend experience with React, Next.js, or equivalent modern frameworks.Familiarity with HRIS, ERP, or people systems data models and processes.Experience at a high-growth or AI-native company.Contributions to developer experience tooling, CLIs, or internal SDKs.Experience building or integrating AI/LLM-powered features — not just experimenting, but shipping to real users.How We WorkWe operate as a small, senior, hands-on team. Engineers own features end-to-end — from design discussion through production monitoring.Code reviews and design reviews are expected for all meaningful changes. We discuss architecture openly, make decisions quickly, and ship frequently.Interview processIf there appears to be a fit, we'll reach out 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, the process to offer may be shorter.