Build and ship AI methods for federal research data with LLMs, NLP, RAG, knowledge graphs.
Benchmark AI against baselines and human reviewers to prove gains in accuracy, reliability, efficiency, cost.
Set standards for trustworthy AI and mentor data scientists through code review and guidance.
ARI builds AI methods for federal research-funding and administrative data, with clients including the NIH. It is a small multidisciplinary team of scientists, analysts, economists, and data scientists experienced with NIH data.
Own the build out of new agents, skills, and platform capability for teams across TLDR.
Build and deploy agents end to end, from design through implementation, evals, and rollout to internal users.
Partner with stakeholders across sales, editorial, and people ops to find where an LLM belongs in their process.
TLDR runs the largest network of tech newsletters in the world, with over 8 million subscribers covering startups, software engineering, AI, and more. Our 31-person full-time team is bootstrapped, profitable, and on track for $35M in revenue this year, with a culture of owning functions rather than slices.
Design, build, and operate LLM-powered applications and services over catalog, sales, and operational data.
Stand up and maintain MCP servers and tool integrations that connect AI models to internal systems.
Own services end-to-end, evaluate emerging AI tooling, and raise the team's AI engineering capability.
Penguin Random House is the leading adult and children's publishing house in North America, the United Kingdom and many other regions around the world. We are committed to quality, excellence, and innovation throughout the entire publishing process, with a vibrant and diverse international community of nearly 300 publishing brands and imprints.
Own AI agents and autonomous workflows powered by LLMs from problem framing through production.
Build RAG pipelines, set evaluation and guardrail standards, and optimize for cost and scalability.
Work directly with client teams to scope problems and deploy AI systems in their environments.
Acceler is a Forward-Deployed Engineer company that takes AI from pilot to production inside client systems. With a practitioner network of nearly 1,000 engineers across the US and India, it's a high-caliber team built on ownership, trust, and rapid learning.
Implement embeddings, vector storage, and retrieval across a large, provenance-tracked evidence base.
Integrate language models so generated text is bound to cited source records, and test for citation failures.
Own prompt and output-schema design, model packaging, versioning, serving, and rollback.
DEFCON AI is an insights company that leverages artificial intelligence, mathematical optimization, data analytics, and software engineering to build resilient optimization systems for complex operations. The company offers a fully remote, results-based environment with a focus on production systems and a strong benefits package.
Develop and deploy cutting-edge AI/ML solutions to enhance the platform and improve student learning experiences.
Design, develop, and optimize LLM-powered agentic systems and APIs for real product use cases.
Collaborate with senior engineers and contribute to evaluation frameworks and MLOps pipelines.
Interview Kickstart specializes in interview preparation and career transitions into high-demand tech fields like AI, ML, and Data Science. Over 17,000 tech professionals have been guided by current and former hiring managers to land coveted positions at companies like Google and Amazon.
Design and deploy enterprise-grade AI solutions, autonomous agents, and multi-agent systems.
Build production-ready AI capabilities using LLMs, LangChain, AutoGen, CrewAI, and MCP.
Collaborate across squads to ensure consistent architectural standards and MLOps/AIOps practices.
Inetum is a European leader in digital services, helping businesses and public sector organizations achieve digital transformation. With 26,000 consultants and specialists across 19 countries, they emphasize proximity, flexibility, and responsibility, generating €2.2 billion in revenue in 2025.
Design and build AI agents and automation to solve real problems across engineering, product, and delivery.
Partner with stakeholders to identify high-leverage opportunities and deliver end-to-end solutions.
Stay current with LLM and agentic frameworks to drive innovation in healthcare technology.
HealtheDGE provides AI-powered operational infrastructure for health insurance companies, helping them modernize operations. The company is experiencing strong market momentum and invests in its people, offering a collaborative culture focused on innovation.
Design and develop AI models, agents, and workflow automation for clinical terminology and content operations, taking them from experimentation to production.
Build agentic workflows combining LLMs, tools, APIs, and retrieval to complete complex tasks, and implement MLOps practices for reliable deployment.
Partner with data science and clinical teams to productionize existing agents and drive continuous improvement with a focus on auditability and human-in-the-loop review.
IMO Health provides clinical terminology solutions for healthcare organizations, enabling accurate data normalization and interoperability. They are a mid-sized company focused on innovation and collaboration, emphasizing a culture of technical excellence and cross-functional teamwork.
Lead end-to-end delivery of complex healthcare AI products, including agentic workflows, RAG systems, and production services.
Collaborate with Product, Engineering, Data, and clinical teams to translate stakeholder needs into validated, access-aware AI workflows.
Own evaluation frameworks, model optimization, and human-review controls to keep high-stakes workflows safe, reliable, and governable.
NeueHealth is a value-driven healthcare company that aligns the interests of health consumers, providers, and payors to make healthcare accessible and affordable. They deliver clinical care through owned clinics and provider partnerships while enabling performance-based care with technology and services.
Design and implement autonomous agents and multi-agent orchestration systems for complex, open-ended tasks.\n- Build and optimize production-grade LLM applications with a focus on reliability, observability, and low-latency performance.\n- Architect advanced RAG pipelines and vector database strategies to provide agents with accurate, real-time context.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies through objective evaluation. The company operates with a distributed, global-first team culture, emphasizing fairness and innovation in recruitment.
Design and deliver production-grade agentic AI systems using Glean, OpenAI/GPT Enterprise, and AWS/GCP.
Own AI agents end to end, from architecture through deployment, monitoring, and iteration.
Implement RAG, tool calling, permissions, and observability to ensure reliable, scalable enterprise AI.
This partner company builds production-grade agentic AI systems for enterprise environments, leveraging Glean, OpenAI/GPT Enterprise, and cloud infrastructure. They foster a collaborative, open-door culture with global projects and tailored learning opportunities.
Own agent definition, problem selection, and the human-in-the-loop contract.
Work hands-on with AI Lab engineers and the CEO to prototype, evaluate, and ship WFM agents.
Own build quality, evaluation, FRDs, commercialization, and design-partner delivery.
Legion Technologies provides an AI-driven workforce management platform that maximizes labor efficiency and employee engagement for hourly workers. It is a remote, mission-driven company with a collaborative, fast-paced culture.
Define end-to-end requirements for AI capabilities, from model behavior to user experience.
Translate model capabilities and technical constraints into product decisions.
Work closely with ML and engineering teams on system design and iteration.
They develop AI-powered email applications and work at the intersection of user needs and model capability. The company is fast-moving and collaborative with a strong focus on technical ownership and innovation.
Develop and improve AI methods, algorithms, and systems across the lifecycle of reliable AI agents.
Create new approaches for simulating, evaluating, and optimizing agent behavior in real-world settings.
Turn research ideas into working systems, prototypes, and production-facing capabilities.
The company builds infrastructure that helps enterprises make AI agents more reliable in production. It is a technical and research-focused team working on AI methods and practical systems.
Owns the architectural direction for Code Metal's AI platform and the team building it.
Builds production-grade inference serving, model gateways, agent harnesses, and context-engineering services.
Instruments the stack end to end and drives experimentation and observability for reliable AI systems.
Code Metal provides automated software engineering using AI and formal verification to produce provably correct code. Founded in 2023 and backed by Accel, Salesforce Ventures, and others, it serves defense and enterprise customers from offices in Boston and San Francisco.
Design, build, and operate generative AI solutions grounded in authoritative source documentation for healthcare clients.
Build document ingestion pipelines, implement guardrails, and develop evaluation frameworks to ensure accuracy and traceability.
Deploy solutions within AWS services and federal security controls while collaborating with project managers, data engineers, and client stakeholders.
Magpie Health Analytics provides secure, trustworthy generative AI solutions that help healthcare clients deliver faster, more consistent access to authoritative program guidance. They emphasize collaboration with cross-functional teams and responsible AI oversight in a culture focused on security and innovation.
Design and improve AI systems for extracting structured reasoning signals from technical interviews.
Build LLM-powered pipelines for semantic analysis, behavioral feature extraction, and evaluation.
Develop scoring, calibration, and benchmarking methods grounded in measurable evidence.
APADCode is an early-stage AI startup building an AI-powered technical interview platform that evaluates how candidates reason and solve problems. The company is a small, early-stage team with a culture of high ownership, direct collaboration, and minimal bureaucracy.
Design and implement RAG pipelines and tool-calling architectures for conversational AI agents in healthcare.
Build production Python code using LangChain and modern LLM frameworks to solve novel healthcare AI problems.
Own end-to-end deployments, monitoring, and customer partnerships in production healthcare environments.
Hippocratic AI is building the first healthcare-only, safety-focused large language model to transform patient outcomes. The company is backed by leading healthcare and AI investors, with a team of physicians, hospital leaders, and AI pioneers from top institutions.