Design and build knowledge graphs and AI agents to structure and utilize knowledge.
Set technical direction and mentor engineers and data scientists.
Collaborate with global teams to turn research into customer features.
Loopio is a software company that builds response management and knowledge management solutions. They are a global, remote-first company with employees across Canada, the UK, the US, and India, known for their supportive culture and award-winning workplace.
Develop machine learning and LLM capabilities for query intelligence and search relevance.
Build agentic search planners and improve model behavior through prompt development and fine-tuning.
Own projects from problem definition to production deployment and collaborate with cross-functional teams.
Atlassian builds software products that help teams collaborate and manage work. The company fosters a flexible and inclusive culture, with employees able to choose where they work and a focus on innovation.
Research and deploy NLP, ML, and GenAI solutions for revenue lifecycle management products.
Partner with engineering and product to take models from experimentation to production at scale.
Mentor teammates and drive evaluation standards while building LLM and RAG-based capabilities.
Conga unifies pricing, quoting, contracting, rebates, and communications so companies run as connected, smarter businesses. Trusted by over 10,000 customers and 50% of the Fortune 100, Conga fosters a culture where colleagues thrive and every voice is heard.
Build new functionality within a fast-moving product, taking ambiguous ideas from design to rigorous experimentation within weeks.
Conduct deep-dive research into state-of-the-art LLM orchestration, retrieval strategies, and data-driven personalization.
Build production-grade ML systems at Twilio scale, leveraging the latest AI development stacks to focus on core differentiation.
Twilio is a cloud communications platform that enables businesses to create personalized customer experiences through APIs and AI-driven solutions. The company is remote-first, serving hundreds of thousands of businesses, and fosters a culture of connection, inclusion, and innovation.
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 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 build production-grade AI agents with LangGraph to automate multi-step workflows across internal teams.
Deploy and scale agents on Amazon Bedrock AgentCore, ensuring security, reliability, and cost efficiency.
Partner with internal teams to identify high-impact workflows and drive adoption through documentation and training.
Wrapbook is an AI platform for production finance, helping finance teams manage payroll, spend, and accounting for film, TV, and commercial productions. Trusted by teams at Netflix and Paramount, the 350+ person company is backed by major investors and focused on using AI to transform how finance teams work.
Lead technical design and delivery of high-impact AI initiatives, including agentic workflows and retrieval systems.
Own projects from concept through production while mentoring engineers and raising engineering standards.
Build production-grade AI systems using LLMs, RAG, and AWS services.
Givzey | Version2.ai is a fully remote, AI-native company that created the Autonomous Fundraising category, deploying Virtual Engagement Officers to help nonprofits scale donor outreach. The company has generated over $20M in fundraising revenue and fosters a culture of technical excellence, mentorship, and ownership.
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.
Own end-to-end product strategy and roadmap for Netomi's Agents platform, tying investments to measurable enterprise outcomes.
Work hands-on with AI labs, build prototypes, design evaluations, and debug production failures to drive faster product decisions.
Collaborate with engineering, research, data science, and go-to-market teams to launch capabilities adopted by global enterprise brands.
Netomi is an agentic AI platform for enterprise customer experience, enabling automation across the customer journey for global brands like Delta Airlines, MetLife, and United. Backed by WndrCo, Y Combinator, and Index Ventures, it focuses on driving efficiency, lowering costs, and delivering high-quality customer experiences.
Design, deploy, and optimize large-scale ML systems for retrieval, ranking, and LLM-powered features.
Lead ML projects from concept to production, improving answer relevance and user experience.
Collaborate with Product, Data Science, and Engineering teams to shape technical direction.
The hiring partner is a technology company focused on building advanced AI systems that help users discover relevant answers from large collections of online conversations. It values innovation, collaboration, and responsible AI development, offering a remote work environment within the United States.
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 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 production-ready AI and LLM-powered applications for nonprofit organizations.
Develop evaluation methods, contribute to open-source tools, and collaborate with field teams.
Take technical ownership across the ML lifecycle and translate research into scalable products.
A mission-driven engineering team developing practical AI systems for healthcare, agriculture, education, and international development. The company values autonomy, collaboration, and technical excellence, working as a small, interdisciplinary team.
Building multi-agent systems and implementing agent-based workflows and AI automation solutions.
Developing and optimizing prompt engineering strategies, including evaluation and iteration.
Integrating LLMs and AI models into cloud-based applications and APIs while researching new AI tools.
Software Mind develops impactful software solutions for global companies, partnering with tech giants and unicorns on transformative projects. The company builds cross-functional engineering teams and embraces a culture of openness, respect, grit, and cooperation.
Develop and enhance AI agents, orchestration, and conversational experiences using Python, LangGraph, and LangChain.
Build scalable enterprise AI platforms with observability, monitoring, and performance tracking.
Integrate AI applications with enterprise systems, APIs, and modern agent communication frameworks.
Miratech is a global IT services and consulting company that helps enterprises and startups innovate and transform digitally. With nearly 1,000 professionals across 25+ countries, it fosters a culture of Relentless Performance and has a 99% project success rate.
Design, build, and deploy LLM-powered agents that detect spam, harassment, and policy-violating content on Quora.
Develop agentic workflows to automate content moderation and user safety tasks at scale.
Evaluate model performance, investigate failures, and refine AI systems for accuracy and efficiency.
Quora is a global knowledge-sharing platform that connects people with expert answers. This role sits on a small, collaborative engineering team with a remote-first culture and a focus on AI safety and content quality.
Design, train, and deploy ML models for text classification, entity extraction, and topic detection.
Build LLM-powered features including RAG, prompt design, and agentic workflows.
Collaborate daily with US-based engineers and productionize models as monitored services.
Tech Holding is a full-service consulting firm that delivers predictable outcomes and high-quality solutions to clients from startups to Fortune 50 companies. The culture is built on deep expertise, integrity, transparency, and dependability, with a team of experienced industry professionals.
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.
Build AI-powered agents and tools end-to-end: identify problems with clients, prototype quickly, evaluate rigorously, and ship to production.
Design and implement LLM integrations including prompt engineering, function calling, structured outputs, and retrieval-augmented workflows.
Work directly with clients to understand workflows, validate AI behavior, and iterate toward production quality.
Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. With over 1,500 firms in 60 countries and nearly $10 trillion in assets on the platform, Addepar fosters a culture of ownership, collaboration, and continuous learning.