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.
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.
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.
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.
Build RL environments, agentic systems, LLM pipelines, and evaluation frameworks for real-world AI use cases.
Develop benchmarks and evaluation harnesses to assess model quality across accuracy, safety, latency, and cost.
Conduct fine-tuning and model experiments, deploy self-hosted models, and document reproducible methodologies.
The employer is an organization focused on applied AI research, building practical and reusable AI systems for real-world use cases. It values curiosity, accountability, innovation, collaboration, and continuous learning in a remote environment.
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.
Conduct research on enterprise agentic AI, including agent memory, continuous learning, safety, and privacy.
Leverage unique access to real enterprise deployments to test hypotheses and advance the state of the art.
Publish at top-tier venues and collaborate with cross-disciplinary teams to influence product decisions.
ServiceNow is the AI control tower for business reinvention, bringing together AI, data, and workflows to help 85% of the Fortune 500 work smarter. The company is a global leader with over 8,100 customers, building an AI-native culture where technology and talent are unstoppable together.
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, train, and evaluate machine learning models end to end, from data and experiment design through training and reporting.
Design reinforcement learning environments, reward functions, and verifiers, and fine-tune language models using methods like PPO, DPO, and GRPO.
Collaborate with domain experts, analyze datasets, and present findings clearly to both technical and non-technical audiences.
EnableComp provides specialty revenue cycle management solutions for healthcare organizations using its unified E360 RCM platform. It is a multi-year Top Workplaces recipient and has been named to the Inc. 5000 list of fastest-growing private companies for eleven years.
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.
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.
Lead the engineering strategy and execution for evaluations of AI agents, owning the core evaluation platform.
Design scalable evaluation infrastructure, APIs, workflows, and production systems across software categories.
Mentor and develop a team of engineers as the technical authority on agentic evaluation.
This company focuses on building credible, scalable evaluations of AI agents from software vendors. It operates as a fully remote, inclusive team with a flexible culture and a focus on professional growth.
Own the intelligence layer of Project Interstellar, building production LLM systems for document intelligence, voice agents, and task orchestration.
Design and maintain prompt engineering infrastructure, model abstraction, RAG layers, and agent orchestration frameworks.
Partner with engineering and domain experts to integrate AI capabilities into a HIPAA-regulated platform from the ground up.
Certum Legal Solutions is a legal managed services organization that provides operational infrastructure, technology, and back-office solutions for personal injury law firms. The company is building a proprietary AI-native system and is assembling a high-caliber team in a greenfield, fast-paced environment.
Research, develop, and maintain production-quality machine learning code for materials science problems.
Collaborate with product, engineering, and research teams to transform AI ideas into scalable, customer-ready capabilities.
Evaluate and improve model performance, reliability, and interpretability across the full feature lifecycle.
The company develops materials-aware AI capabilities for scientific and industrial applications. They value autonomy, collaboration, and continuous learning in a remote environment.
Design retrieval architectures and build AI-powered agents for healthcare intelligence.
Own production deployments and on-call support for HIPAA-compliant systems.
Partner with product, data science, and clinical teams to deliver AI at scale.
Cohere Health builds a clinical intelligence platform with AI-powered solutions that streamline payer-provider decision-making in healthcare. The company has been recognized on the Inc. 5000 list and as a top LinkedIn startup, with a collaborative, empathetic culture.
Design and develop specialized AI agents using Generative AI, LLMs, and agentic frameworks like LangChain and Semantic Kernel.
Build MCP servers and integrate AI applications with event-driven architectures, ensuring secure and traceable decisions.
Implement Human-in-the-Loop workflows and apply PromptOps practices for scalable, secure, and high-impact AI solutions.
The hiring company is a technology organization in Brazil focused on building AI-powered applications and agentic systems. It fosters a collaborative and international culture, with fully remote work and opportunities to work on innovative AI technologies.
Design, develop, and maintain AI-powered software solutions across the full development lifecycle.
Work with backend stacks like Python, Node.js, .NET, and Java, plus modern frontend frameworks such as React or Angular.
Build and integrate AI agents, RAG pipelines, and LLM-driven products into production environments.
Cresteo is a nearshore tech services company on a mission to be the world leader in people-first and honest software development. Our small, high-trust team values transparency, profit-sharing, and fearless innovation while working with US-based clients and international teams.
Lead the engineering foundation behind reliable, measurable, and scalable AI-powered features.
Build evaluation frameworks, observability tooling, and diagnostic infrastructure for AI agents in production.
Combine hands-on software engineering with technical leadership and people management.
The company builds AI-powered products with a focus on reliability, scalability, and evaluation infrastructure. It operates as a fully remote, globally distributed team with an ownership-oriented culture.
Collaborate directly with customers as an embedded technical expert, designing and deploying agentic AI solutions.
Quickly understand new industries, data, and systems to identify high-value AI and agentic workflows.
Build proof-of-concepts and production solutions using MCPs, agent frameworks, and tool-using LLMs.
We are a fast-growing company that helps customers turn AI ambitions into real production outcomes. We are fully remote with a 32-hour workweek and a collaborative, trust-based culture.