Conduct AI research on enterprise agentic systems, focusing on agent memory, continual learning, safety, and privacy.
Work with real enterprise deployments to test hypotheses and advance the state of the art in AI.
Publish findings at top-tier venues and influence technical decisions across product and engineering teams.
ServiceNow is a global cloud platform company that uses AI to connect people, systems, and processes for enterprise business reinvention. The company serves 85% of the Fortune 500 and fosters an AI-native culture where technology and talent work together.
Develop and improve AI methods, algorithms, and systems across the lifecycle of reliable 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 is a research-focused team developing methods and systems to make AI agents more reliable in production. It operates as a small team with a culture of original research, experimentation, and close collaboration with product and engineering.
Build reinforcement learning and agent environments for real customer and Frontier lab use cases, including task specifications, scoring, and evaluation.
Develop benchmarks and evaluation harnesses to measure model and data quality across accuracy, robustness, safety, latency, and cost.
Run fine-tuning, adapter, and other model experiments to evaluate how data and methods influence model behavior, and deploy local or self-hosted models for evaluation and inference.
Appen has been a leader in AI training data for over 30 years, specializing in human-generated data to train, fine-tune, and evaluate models across generative AI, LLMs, computer vision, and speech recognition. They support model development through an AI-assisted data annotation platform and a global crowd of over 1 million contributors in more than 200 countries, fostering a culture of innovation, collaboration, and humility over ego.
Design, build, and deploy AI agents that automate Mind Moves' internal operations, from contractor onboarding to market-rate research.
Decompose workflows into agent architectures—skills, tools, evals, memory, and orchestration—and build evaluation frameworks that measure and improve agent quality.
Own the full lifecycle from identifying workflows to prototyping, deployment, monitoring, and iteration, creating reusable infrastructure and documentation.
Mind Moves is a women-owned Washington, D.C.-based consultancy that helps businesses and governments design, build, and deploy human-in-the-loop AI solutions. It is a small, entrepreneurial team of AI pioneers that has delivered products serving millions of users and worked with Fortune 500 corporations and large government entities.
Build the Learning Gym, a sandboxed environment for training and evaluating AI agents on real Niural workflows with ground-truth reward signals.
Engineer verifiers, run reinforcement learning loops, and establish honest baselines to prove agent improvements generalize.
Write first-author research papers and internal technical reports, and represent the work externally through preprints and talks.
Niural is a global payroll, Employer of Record (EOR), Agent of Record (AOR), and Contractor Management platform. It is a relentlessly ambitious team focused on building foundational internet infrastructure for the AI era.
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.
Lead exploration and application of Large Language Models and Generative AI into core product lines.
Translate the latest research into high-performing systems that enhance customer experiences.
Collaborate with cross-functional teams to set strategy and deploy ML solutions with real business impact.
Replicant is the industry leader in voice AI for customer service, providing automated phone bots for enterprises like AAA and Fanatics. Founded in 2017, the company is backed by top-tier Silicon Valley investors, has offices in the SF Bay Area, Toronto, and New York, and maintains a distributed team across the US and Canada.
Design and build enterprise-grade agentic AI platforms and LLM-powered applications.
Define reference architectures for RAG pipelines, multi-agent orchestration, and enterprise integrations.
Implement observability, guardrails, and responsible AI practices for production deployment.
Brillio is one of the fastest growing digital technology service providers, partnering with Fortune 1000 companies on digital adoption. It employs world-class professionals known as 'Brillians' and has earned Great Place to Work® certification repeatedly.
Design and deliver production-grade agents that investigate, reason, and act on live observability data.
Own agent work from rough prototype to production, including evals.
Extend the agentic workspace with new canvas capabilities, MCP server, and skills.
Honeycomb provides an observability platform that helps engineers understand and debug complex systems. It is a fully distributed company of over 200 people, with a culture that values impact, autonomy, and inclusivity.
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.
Develop, configure, deploy, and optimize AI agents using Cresta's AI platform and tools.
Build AI agent integrations with external systems such as APIs, databases, and CRMs to ensure seamless workflow integration.
Collaborate with customers and internal stakeholders to gather technical requirements and translate business needs into AI agent solutions.
Cresta builds a unified AI platform that combines conversational AI agents, real-time human agent augmentation, and conversation intelligence to drive revenue and efficiency for customer experience channels. Born from Stanford AI Lab, the company has raised over $270 million from top investors and is led by AI industry veterans.
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.
Architect platform-level AI, knowledge graph, and data systems for enterprise supply chains.
Lead hands-on technical development in agentic AI and mentor engineers.
Evaluate emerging technologies to drive product innovation and scalable design.
Kinaxis is a global leader in modern supply chain orchestration, powering complex supply chains with an AI-infused platform. With over 2,000 employees worldwide, it is a top employer with a collaborative culture.
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.