Research Intern, Inference (Fall 2026)
As an AI Infrastructure Engineer at Together, the responsibilities include participating in on-call rotation to respond to production incidents, building and running infrastructure using Ansible, Terraform, and Kubernetes to support scaling to a large number of concurrent users, building monitoring systems to ensure high-quality service, designing and implementing operational processes such as deployments and upgrades, debugging production issues across all services and stack levels, identifying improvements for product architecture in terms of reliability, performance, and availability, and planning the growth of Together AI's infrastructure.
Agentic Solution Engineer
Design and write high-quality prompts for LLM-based agents (GPT-class models preferred). Build agentic tools and workflows using Netomi's no-code platform. Integrate external and internal APIs, including authentication, data mapping, and error handling. Implement unit tests, debug issues, and ensure reliability of agent workflows. Apply engineering best practices and design patterns such as retries, timeouts, idempotency, and lazy loading. Optimize agents for performance, cost, and fault tolerance. Collaborate with Product, QA, and Delivery teams to ship production-grade agentic solutions.
Agentic Product Analyst
As an Agentic Product Analyst at Netomi, you will be responsible for designing, architecting, and deploying large-scale Agentic AI solutions for enterprise customers. This includes leading discovery sessions with customers to understand business processes, identifying automation opportunities, and designing agentic orchestration strategies using Netomi's AI platform. You will build detailed solution blueprints covering workflows, data exchanges, escalation logic, analytics, and agent lifecycle design. Defining end-to-end Agentic AI architectures and working with customer technical teams to map integration dependencies are also key tasks. You will own the creation of integration design documents, support Integration Engineers during implementation, and ensure agent workflows comply with enterprise standards. Collaboration with Product & Engineering to translate requirements into features, serving as product owner during deployment, validating solution behavior with QA, conducting user-experience reviews, training customer teams, and ensuring projects deliver on time with measurable impact also fall under your responsibilities. Additionally, you are expected to act as a trusted advisor to customer stakeholders, present architectural recommendations, drive continuous improvement, and maintain deep expertise in agentic AI, LLMs, workflow orchestration, and enterprise systems.
Member of Technical Staff (Machine Learning Engineer)
Translate cutting-edge research into production-ready machine learning systems. Design, build, and deploy end-to-end ML models and pipelines. Develop and optimize models for image and video processing. Own the full ML lifecycle including experimentation, training/fine-tuning, evaluation, and deployment. Rapidly prototype using open-source models and adapt them for product needs. Conduct experiments, analyze results, and iterate to improve performance. Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale. Participate with advancements in machine learning and apply them to continuously improve products.
Warehouse Supervisor (Temporary)
Utilize proprietary software to provide accurate input and labels for healthcare and administration projects, ensuring high-quality data for AI model training. Deliver curated, high-quality data for scenarios involving patient care coordination, medical billing, administrative workflows, and healthcare operations. Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies. Assist in designing and improving efficient annotation tools tailored for healthcare and administration data. Select and analyze complex problems in healthcare and administration fields aligned with your expertise to enhance AI model performance. Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.
Software Engineer
Build end-to-end features across backend and frontend that directly impact customer revenue. Work closely with design, product, and GTM to ship features from idea to production. Translate real-world workflows, including calls, scheduling, and dispatch, into scalable systems. Improve system reliability, performance, and developer velocity as the system scales. Learn fast by working directly with customers and iterating based on real usage.
Engineering Manager, RLE
Build and scale reinforcement learning environments and platforms behind them; drive architecture for scalable, reliable, extensible environment systems and data generation pipelines; partner with Research, Product, and Ops teams to turn ambiguous needs into production systems; build modular, plug-and-play domains that integrate cleanly with training and evaluation loops; improve reliability, observability, performance, and data quality of systems.
Senior Staff Engineer, Software Autonomy (R5125)
The Senior Staff Software Engineer, Autonomy functions as a hands-on technical lead and subject matter expert, collaborating with teammates and customers to build edge-AI and autonomy software for platforms across sea, air, and space. Responsibilities include working closely with customers to understand requirements, writing code, developing new capabilities, and ensuring successful software/hardware integration. The role involves mentoring teammates, designing tactical autonomy algorithms for unmanned aircraft to perform complex missions across various domains, developing high-performance software modules for planning, decision-making, and behavior execution in dynamic and adversarial environments, implementing and testing behavior architectures for multi-agent coordination and target engagement, and integrating hybrid autonomy approaches blending classical and learning-based methods. The engineer will collaborate with cross-functional teams to ensure seamless integration on real-world platforms, deploy capabilities to platforms, participate in field tests and flight demos, analyze mission data to diagnose failures and optimize models, contribute to R&D and autonomy roadmapping, support defense-focused programs and customer needs by adapting solutions, provide software handover and training to customers, and develop and maintain technical documentation. Travel is required for deployment, training, and flight testing, typically around 10-15% to different office locations and ~30% for customer site visits.
Legal Advisor (US Bar Admitted) - Freelance AI Trainer
Contributors may generate prompts that challenge AI, evaluate AI-generated solutions for correctness, assumptions, and logic, improve AI reasoning to align with first principles and accepted standards, and apply structured scoring criteria to assess multi-step problem solving.
Materials Engineer & Python Expert - Freelance AI Trainer
You design computational material science problems to challenge a frontier AI model with problems that have verifiable answers by code and require specialized tools like ObsPy, instaseis, pyrocko, MITgcm, flopy/MODFLOW, or others. You pick an anchor tool and design a problem focusing on its waveform-processing kernels, geophysical inversion routines, sub-surface flow solvers, or community-validated data pipelines. You write a Python reference solution, supply input files and model or domain definitions where necessary, decide the numerical answer and required tolerance, test the problem against the AI model in batches of parallel attempts, tune the problem difficulty to achieve a low pass rate, and submit the task to a senior reviewer for quality feedback. Calibration involves tuning the problem by rewriting scenarios, tightening parameters and solver tolerances, and observing the model's behavior, which builds deeper command of the tool and understanding of how the AI model navigates complex geophysical problems.
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