Own the design and defense of frontier model evaluations across reasoning, coding, agents, tool use, and multi-modal.
Build benchmark packages with expert-verified ground truth, multi-model headroom results, and rigorous QC.
Recruit, calibrate, and review a pool of subject-matter experts in coding, agentic/tool-use, and STEM/reasoning.
Anyone AI measures frontier model capability through expert-verified evaluation packages. The company operates as a remote team with a focus on rigorous benchmarking and lab collaboration.
Lead technical discovery with foundation model labs, frontier AI teams, and large enterprises to understand model objectives and constraints.
Design end-to-end solutions across the post-training stack including SFT data curation, RLHF/DPO pipelines, custom benchmarks, and LLM-as-judge systems.
Author technical proposals, run workshops and POCs, and serve as ongoing technical advisor during delivery.
Innodata is a global data engineering company focused on enabling responsible AI advancement through data, evaluation frameworks, and human expertise. With a 36+ year legacy, they provide high-quality data solutions to foundation model labs, hyperscalers, and enterprise AI teams.
Build agent harnesses in Python using LangChain and LangGraph, including tool-calling and structured outputs.
Develop evaluation frameworks with golden datasets, LLM-as-judge, and regression suites, wiring them into CI.
Collaborate with data engineers on Snowflake-backed retrieval patterns like Cortex Analyst and Search Services.
Kobie is a loyalty solutions partner that helps brands build emotional connections with their consumers. Named a Top Workplace in the USA, they offer a flexible remote culture with a focus on collaboration and growth.
Own AI evaluation methods and operations for Figma's AI-powered experiences, defining quality dimensions and designing measurement frameworks.
Build and maintain evaluation frameworks, rubrics, golden datasets, and quality bars using human and automated approaches.
Produce clear readouts and dashboards to enable stakeholders to make confident shipping decisions.
Figma is on a mission to make design accessible to all, empowering teams to bring ideas to life through collaborative design and prototyping tools. With a growing team of passionate creatives and builders, Figma fosters a culture of growth and inclusivity.
Build, ship, and own product features end-to-end using cutting-edge AI/ML techniques.
Apply classical ML and LLM-based approaches like RAG, prompt engineering, and fine-tuning to enhance the audit and risk platform.
Collaborate with cross-functional teams in an Agile environment to deliver scalable, production-quality code.
Optro is a leading audit, risk, ESG, and InfoSec platform trusted by over 50% of the Fortune 500. The company has been named one of the 500 fastest-growing tech companies in North America for seven consecutive years, fostering a culture of innovation and collaboration.
Design and build AI-enabled features for education products, working with stakeholders to understand real workflows.
Integrate LLM APIs and develop evaluation approaches for quality, consistency, and reliability.
Build prototypes quickly, test against real use cases, and productionize successful approaches.
We are a global EdTech company building a suite of AI-enabled products for students, teachers, and education partners to support better learning outcomes at scale. Our team fosters a culture of experimentation and disciplined engineering.
Develop and improve NLP systems and language model-powered experiences.
Fine-tune and optimize language models for domain-specific use cases and build evaluation frameworks.
Deploy and maintain production-grade ML systems on GPU infrastructure with a focus on scalability and safety.
BetterHelp removes barriers to therapy and makes mental health care accessible globally. Founded in 2013, it is now the world's largest online therapy service with over 30,000 licensed therapists, and it invests deeply in employee well-being and professional development.
Build and iterate on consumer-facing AI features powered by large language models (LLMs) and generative AI systems
Collaborate with engineers across the AI stack including prompt engineering and agentic workflow optimization
Run structured experiments and monitor production AI systems to optimize latency, cost, and scalability
Quora is a global knowledge sharing platform with over 300M monthly unique visitors, connecting people to share insights and learn. Poe provides a platform for users to chat and build with AI language models. They are a remote-first company with a culture rooted in transparency and experimentation.
Build, train, and improve machine-learning models for production use.
Develop evaluation and feedback loops that measurably improve model performance over time.
Evaluate new models and techniques, bringing the best into production.
Allocate transforms private market investing by enabling RIAs and family offices to discover, model, and manage private market exposure. The company provides a platform with curated fund and co-investment opportunities, and values meritocracy, civil discourse, and continuous improvement.
Design and deliver high-quality AI evaluation data initiatives, from proposals through pilot execution and production readiness.
Recruit and manage subject-matter experts across technical domains, ensuring rigorous quality control frameworks.
Act as key interface with AI lab partners, converting pilots into scaled production engagements.
Jobgether uses AI-powered matching to connect candidates with roles quickly and fairly. They are a remote-first company that shares top-fitting candidates with hiring partners.
Research data collection strategies and design high-impact data slices that uncover model failure modes.
Model annotator behavior and design experiments to optimize instruction clarity and reward signal reliability.
Develop metrics and frameworks for evaluating dataset quality, diversity, and impact on downstream model alignment.
Surge AI builds a platform that powers the most powerful AI models in partnership with companies like Anthropic, Google, Microsoft, and Meta. They are a profitable, bootstrapped company focused on human intelligence and data quality.
Own end-to-end Machine Learning (ML) system execution including data pipelines, training, and deployment.
Fine-tune and adapt models using state-of-the-art methods like LoRA and DPO.
Architect scalable inference systems and collaborate closely with application engineering.
This company develops advanced production-grade machine learning systems. The team is small and high-trust, with a culture of ownership and pragmatism.
Build and improve ML components across data, training, evaluation, and inference.
Implement evaluation and testing to understand model behavior.
Debug model issues, performance problems, and production incidents.
This company builds core ML components for large-scale production systems. They emphasize real-world learning, iteration, and collaboration with senior engineers.
Design, build, and operate multi-agent workflows and tool-enabled agents for resilient production pipelines.
Architect and maintain end-to-end RAG systems covering document ingestion, chunking, embedding, retrieval, and answer synthesis.
Define and own evaluation frameworks for generative outputs, including automated metrics, LLM-as-judge, and hallucination detection.
Mitratech builds world-class products that simplify operations in Legal, Risk, Compliance, and HR functions. With over 35 years of experience, we serve 20,000 client companies globally, including 30% of the Fortune 500, and foster a diverse, inclusive culture centered on individual excellence and learning.
Design, develop, and deploy production-grade AI-powered backend systems integrating LLMs and traditional ML models.
Integrate and optimize vector databases for RAG pipelines, and write clean, well-structured Python code.
Debug complex cross-layer issues and collaborate with product and engineering teams to deliver cohesive solutions.
We are a fast-growing product company integrating cutting-edge AI capabilities into our core offering to deliver exceptional value to customers. Our small, fast-moving team works on practical, real-world AI applications with high autonomy.
Design and build the agent execution harness, owning the orchestration layer that routes inputs, manages context, and handles multi-step agentic workflows at scale.
Ensure reliability, observability, and fault tolerance in production AI systems while optimizing for latency and cost.
Lead eval engineering and prompt infrastructure to maintain agent quality and drive data-informed decisions across model updates.
ServiceNow is an AI platform company that automates workflows and helps businesses reinvent themselves through its AI control tower. It serves 85% of the Fortune 500 and fosters an AI-native culture focused on innovation and talent.
Lead and scale a team building next-generation AI evaluation infrastructure.
Define strategy and roadmap for evaluation platform including benchmark design and quality monitoring.
Drive innovation in evaluation methodologies like agentic and multi-turn assessment.
ServiceNow is the AI control tower for business reinvention, helping 85% of the Fortune 500 work smarter. The company fosters an AI-native culture where technology and talent are unstoppable together.
Architect and build production systems across a multi-language stack including C#/.NET, Python, and TypeScript.
Design and drive adoption of offline and online evaluation frameworks for AI components, including test suites, golden datasets, and regression monitoring.
Partner with engineering leadership to surface systemic risks in AI features and lead architecture reviews for major initiatives.
RxSense is a healthcare technology company that provides platforms and solutions to improve the management and access of cost-effective pharmacy benefits. As a leader in SaaS technology for healthcare, they offer innovative solutions with integrated intelligence on a single enterprise platform.