Builds and scales AI agents for autonomous patient recruitment, screening, data collection, and 24/7 support in clinical trials. Focuses on ML models, multi-channel LLM deployment, and integrating legacy healthcare systems.

Leads development of proprietary AI reasoning model TRAM for interpreting global trade law, building data pipelines, fine-tuning LLMs, and evaluation frameworks for high-speed, accurate compliance determinations. Requires AI product experience, especially RAG systems and model fine-tuning.

Designs and implements novel causal inference algorithms and production systems for marketing attribution challenges at enterprise scale. Requires 5+ years shipping research code, strong math/stats background, Python proficiency, and customer collaboration.

Leads the architecture, roadmap, and production execution of GenAI and agentic machine-learning systems at enterprise scale. The role requires 10–12+ years of applied ML experience, expertise in retrieval and large-scale systems, and the ability to mentor senior technical teams.

Build and deploy applied machine learning solutions for enterprise customers using large language models. The role requires experience leading ML teams, setting technical direction, working cross-functionally, and applying Python and modern ML frameworks to large-scale training and inference.

Designs, builds, and iterates on AI/ML models for personalization, query understanding, and content discovery. Requires 5+ years in ML, deep learning expertise (PyTorch/TensorFlow/JAX), Python, and full ML lifecycle ownership.

Designs, builds, and deploys generative AI systems including LLM-based code reviews, agentic workflows, and RAG pipelines for developer productivity tools. Requires 3+ years in ML/LLM production systems, Python/TypeScript proficiency, and AI frameworks like LangChain.

Develops and deploys AI/ML models including fine-tuning LLMs and multi-modal systems from concept to production. Requires strong AI/ML skills from top CS/EECS/Math/Physics programs and proven production experience.

Partners with government agencies to develop and deploy GenAI applications using OpenAI API, from strategy to production. Requires 7+ years public sector technical consulting, TS/SCI clearance, and ML implementation experience.

Build and deploy machine learning systems powering an AI-native ITSM platform, including ticket understanding, knowledge extraction, workflow automation, and predictive insights. The role requires strong Python and ML engineering skills, experience with modern ML frameworks and MLOps, and a bachelor’s or master’s degree in a relevant field.

Builds and deploys production-grade AI agents and workflows for business functions like marketing, recruiting, and product. Requires 3+ years experience shipping AI/ML apps, including LLM systems, with strong Python/TypeScript skills.

Designs and builds ML systems for real-time fraud detection, including data pipelines, model deployment, and backend services in Go/Python. Requires 5+ years software engineering with applied ML experience on large datasets.

Builds and deploys language model-powered systems for cyber national security applications, including fine-tuning LLMs, RAG systems, and production inference. Requires 4+ years ML experience, Python/PyTorch proficiency, and LLM post-training expertise.

Architects and leads development of scalable ML training infrastructure, including scheduling, storage, networking, and reinforcement learning systems. Requires proficiency in Go, Kubernetes expertise, distributed systems knowledge, and experience with cloud providers and ML workloads.

Leads the development and productionization of AI-powered sustainability reporting features using LLMs, embeddings, and related machine-learning technologies. Requires 5+ years of software engineering experience, including 2+ years building AI products, strong full-stack skills, and London office attendance four days per week.

Designs and implements AI solutions including ML models and LLMs to automate financial workflows and provide real-time insights in an accounting platform. Requires strong ML/DL/NLP expertise, Python, PyTorch/TensorFlow, and production deployment experience in a fast-paced startup.

Builds and optimizes scalable ML inference infrastructure using Kubernetes and GPU resources to deploy production AI models with low latency. Collaborates with ML research and product teams on model serving, orchestration, and compute efficiency.

Builds and optimizes multimodal LLM-based AI agents for enterprise conversations, integrating with systems via APIs and automating high-stakes workflows. Requires 3+ years in AI engineering, Python/PyTorch proficiency, and experience with LLMs or vision models.

Builds, deploys, and optimizes enterprise-grade AI agents for high-stakes conversations, integrating with enterprise systems and fine-tuning LLMs. Requires 3+ years in AI engineering or NLP with Python, PyTorch/TensorFlow proficiency.

12-week fellowship for PhD/MSc STEM graduates to gain hands-on experience in AI engineering, product development, and research. Fellows develop/deploy AI agents using LLMs/RAG, optimize models, and work on enterprise projects with mentorship from AI leaders.

Builds foundational ML platform infrastructure including model serving pipelines, GPU scheduling systems, and CI/CD for large-scale multimodal AI models. Requires 5+ years in distributed systems with expertise in Python, Kubernetes, and AWS.

Build and scale high-performance software and distributed reinforcement-learning systems for LLM post-training. The role combines production engineering, research tooling, algorithm optimization, and collaboration across infrastructure and scientific teams.

Develops and optimizes diffusion models and generative AI for fashion design software. Conducts research, implements techniques for design quality and controllability, and deploys to production. Requires Master's/PhD, 3+ years experience, PyTorch proficiency.

Build, scale, and maintain complex AI/NLP models for the Verneek AI platform, focusing on production deployment of large-scale systems. Requires 3+ years Python/PyTorch experience and BSc in CS; NLP expertise preferred.

Develops methods for AI agents to self-improve post-training through prompt optimization, continual learning from long-horizon tasks, hypothesis testing, and scalable experiments. Requires expertise in LLMs, agent frameworks, and impactful research track record.

Staff Machine Learning Engineer responsible for architecting and operating production-grade ML systems, NLP and Generative AI applications, and end-to-end MLOps on AWS. The role requires 8+ years of experience, strong software engineering fundamentals, and expertise in observability and scalable model deployment.

Develops, deploys, and optimizes production AI systems using LLMs, NLP, and machine learning tools for quant research and market applications. Requires at least two years of hands-on AI or deep learning experience and familiarity with production model deployment.

Builds and improves AI agents and workflows for automating enterprise operations like IT, HR, and finance. Requires 4+ years software engineering with applied AI focus, full-stack skills in TypeScript/Node.js/React, and strong product sense.

Build scalable voice interface features through ML prototyping, infrastructure development, and inference optimization. Requires Python fluency, LLM expertise, and startup experience.

Develops and trains large-scale diffusion models for image/video generation, controllability modules like IPAdapters/ControlNets, and novel research techniques for production. Requires proven experience with image/video models at scale and deep learning frameworks.

Develops low-latency, high-throughput inference services for OCR and multimodal models, optimizing batching, kernels, and autoscaling while evaluating serving frameworks. Requires 3+ years in performance engineering or ML systems with strong Python and GPU experience.

Develops and fine-tunes specialized vision and language models for document understanding, including OCR, layout, tables, and charts. Requires 3+ years ML experience with PyTorch/JAX and strong engineering focus; onsite in San Francisco.

Develops and optimizes transformer-based vision-language models for physical security, owning full-cycle training, fine-tuning, and deployment optimization. Collaborates cross-functionally to integrate models into the platform using PyTorch/TensorFlow and advanced AI techniques.

Develops state-of-the-art agentic AI systems for issue triage, debugging, and predictive analytics using Sentry's error datasets. Requires 4+ years experience (with MS/PhD) or 6+ (with Bachelor's), Python, PyTorch expertise, and production ML deployment skills.

Builds AI systems for voice-first interfaces, audio intelligence pipelines, and real-world conversation analysis using Python/TypeScript and ML tools like PyTorch/OpenAI. Deploys production LLM systems with customer focus in NYC office.

Builds and debugs AI agent infrastructure for healthcare automation, including prompt engineering, runtime issue tracing, evaluation datasets, simulation tooling, data pipelines, and observability dashboards. Requires 2-7 years experience with production LLMs/AI agents and TypeScript proficiency.

Builds state-of-the-art vision models and novel LLM techniques for document processing infrastructure. Monitors production models, runs experiments, and owns large product areas in a high-impact founding role.

Builds production AI agents and workflows for governance, risk, and compliance, fine-tuning LLMs on proprietary data for high-accuracy tasks like regulatory analysis and risk assessment. Requires 3+ years applied AI experience with production ML systems emphasizing explainability and responsibility.

Builds AI-powered product features and backend services for intelligent workflows in Linear's product development platform. Collaborates with product/design to integrate foundation models, optimize prompts, and architect reliable AI infrastructure using React, GraphQL, Node, and Temporal.

Bridge research and production to build agentic LLM and NLP systems for finance and legal workflows. Own experiments combining latest research with customer use cases while embedding in the full software development lifecycle.

Leads the architecture and development of production AI products and a centralized AI platform for accounting automation. The role requires deep Python and backend engineering expertise, scalable system design, and experience with LLM applications, RAG, integrations, and technical leadership.

Build and own core AI agent features and SDKs for an autonomous identity platform. Work across the stack (React, GraphQL, Python/Flask) and mentor engineers as the team scales.

Staff AI Software Engineer builds and scales AI systems including PromptQL AI assistant, data engine, and runtime infrastructure for enterprise reliability. Requires 6+ years experience with AI/ML, distributed systems, LLMs, Python fluency, and technical leadership.

Junior Research Scientist develops and refines ML architectures and LLMs for conversational AI in housing/healthcare, applies advanced math/ML to predict behaviors and optimize interactions. Requires PhD in math/physics/CS or related, strong ML foundation, and onsite work.

Build and improve production generative AI and multi-agent features across the full stack, using LLMs to solve product problems. The role requires strong programming experience, hands-on LLM prompting or GenAI implementation, and a product-oriented approach.

Build and post-train frontier AI models at scale, bridging research and production through scalable training software, distributed infrastructure, and performance optimization. The role requires strong software engineering skills and experience with large-model training and post-training.

Designs, develops, and maintains ML systems for content recommendations, search, spam detection, and labeling using Bluesky's social graph. Requires 3+ years in ML/data science focused on recommendations/search, Python/PyTorch proficiency, and rapid experimentation skills.

Build and optimize high-performance inference infrastructure for OpenAI's multimodal models handling image, audio, and other non-text inputs at scale. Collaborate with research and product teams on low-latency production systems using GPU workloads and inference tooling.

Develops cutting-edge perception models using fused sensor data for autonomous vehicles, focusing on joint detection/tracking and embeddings for downstream systems. Requires MS/PhD in CS, PyTorch experience, and production deployment skills.

Build and deploy scalable NLP and LLM solutions for voice agents, classification, information retrieval, and agentic applications. The role requires 3+ years of machine learning and NLP experience, strong Python/PyTorch skills, and experience with production model deployment.