Learn, maintain, and improve our synthetic data pipeline and automated training system.
Take over a model and improve it with an agent loop that generates its own data.
Build closed loops where agents train detectors, test against validation sets, and improve with little human input.
CVEDIA builds computer vision models and applications that run on server and edge hardware using synthetic data. We are a small, fully remote team that uses AI agents across the company.
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 and improve computer vision and 3D perception models that detect and assess infrastructure from LiDAR and imagery.
Develop LLM-powered products like agentic workflows, MCP servers, and AI copilots for customer tools.
Own models end-to-end, from data and training through evaluation, deployment, and monitoring in production.
Cyvl is a Physical AI company building purpose-built sensors, computer vision, and AI to turn every drive into current data for infrastructure. We're a fast-moving Boston startup with 500+ cities using our platform, and a culture of ownership, intensity, and care.
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.
Design and deploy AI agents that automate sales, operations, and support workflows.
Own technical delivery end-to-end, from architecture to production and post-launch improvements.
Work directly with clients to understand workflows and explain technical tradeoffs.
Stello is an AI transformation firm that partners with mid-market and enterprise companies to automate repetitive work with AI agents. They work across sales, operations, and customer support, deploying solutions inside existing client tools.
Build tools for understanding traces, evaluating agent behavior, and turning results into improvements.
Run experiments on Mastra's primitives to find where they fall short and improve configuration and behavior.
Help turn findings into capabilities developers can use in their own applications.
Mastra is the open-source TypeScript framework for building AI agents. We're a small, fully remote team backed by Y Combinator and Spark Capital with $35M raised.
Take technical ownership of our content and design factory: tooling selection, automation pipelines, quality management, and agent orchestration.
Design and develop complex multistep content and design creation workflows and interfaces using AI model harnesses and tools like AirOps and n8n.
Reduce manual overhead systematically by building automations and agent workflows that replace repetitive processes.
Platform Engineering is home to the world's largest community of platform engineers, connecting thousands of professionals through events like PlatformCon. We are a small, low-ego team with a strong async culture, enabling a community of over 35,000 platform engineers worldwide.
Prototype and test ideas for applying AI to data and marketing workflows.
Develop and ship production-ready AI applications in close collaboration with product and engineering teammates.
Make architectural and framework decisions for LLM-based systems and build data agents that answer analytics questions.
This is a Series D marketing technology company focused on building AI experiences that help teams use data to improve marketing workflows. They are a small, fast-paced product and engineering team within a venture-backed startup environment.
Own agent quality end-to-end for Bliro's chat and voice agents, including prompting, context, and model evaluation.
Build eval sets, LLM judges, and benchmarks to measure quality, latency, and cost with statistical rigor.
Establish a repeatable process for improving agent quality and set the long-term technology roadmap.
Bliro builds an AI assistant that handles desk work for field sales teams, with over one million customer touchpoints documented. Backed by leading investors and trusted by German Mittelstand companies, it's a small, high-performing team that values ownership and continuous improvement.
Design, build and operate production AI agents, including an autonomous coding agent that works from Jira and Slack, opening PRs and fixing CI failures.
Build the retrieval and context layer behind our AI brain: embeddings, semantic search, knowledge-graph modeling, and integration with Snowflake and internal docs.
Harden agents against prompt injection and over-broad permissions, and drive cost and latency down using caching and structured outputs.
Weedmaps is a global leader in the cannabis industry, providing a platform for consumers and businesses. The company has a collaborative culture focused on innovation and community, serving the U.S. and worldwide.
Build AI applications, agents, skills, connectors, and workflow automations that solve business problems.
Translate ambiguous business needs into AI-native workflows and own engineering from discovery to production launch.
Work closely with internal teams to embed AI solutions and drive measurable gains in quality, speed, and cost.
Reddit is a community of communities built on shared interests, passion, and trust. With 100,000+ active communities and about 130 million daily active visitors, it is one of the internet's largest sources of information.
Build and ship production AI systems for the core finance workflows.
Own evals: metrics, test datasets, and monitoring of quality, cost, and latency.
Iterate end-to-end on AI products, from data pipelines to deployment.
Sibill is an AI-powered platform that unifies invoicing, payments, treasury, and accounting for SMEs and accountants in Italy. Backed by €12M from Creandum, the company serves over 5,000 businesses and 300+ firms with a team of over 130 people.
Build evaluations to measure and improve AI reasoning in complex, high-stakes decisions.
Collaborate with engineers, product, and domain experts to turn observed failures into testable improvements.
Own the quality of shipped systems, from code reviews to monitoring and integration.
Elicit builds AI systems that help research and business teams make evidence-based decisions on high-stakes questions. They are a remote-friendly, collaborative team that values rigorous thinking, experimentation, and in-person retreats.
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.
Build the geometry and data core of a new BIM authoring tool.
Develop AI agents that can plan and edit real building models.
Create generative design capabilities that account for building codes and client constraints.
They build AI-first software for architecture and construction, creating a new BIM authoring tool for AI agents. As an early-stage team, they value generalist engineers comfortable working across the stack and willing to grow into leadership roles.
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.
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 realistic electrical engineering tasks based on electronics development, circuit analysis, and electrical systems design.
Create and validate electrical schematics, PCB layouts, and technical specifications for AI evaluation.
Review AI-generated designs for technical accuracy and establish reference solutions.
We create high-quality training and evaluation data for frontier AI models. We are a flexible, remote-first organization assembling a team of expert contractors to advance AI systems.
Study how engineers and customers use Archie in the field, identify where it succeeds or fails, and turn observations into actionable evaluations.
Recreate real-world engineering tasks and failure modes in repeatable environments for development teams.
Build and refine evaluation methodologies, including automated judges and human evaluation processes, to align with expert judgment.
P-1 AI is building Archie, an AI engineer agent for the physical world that works alongside human engineering teams. The company recently raised a $50 million Series A led by NEA and is driven by the mission of building superintelligence for engineering.
Own the vision for applied AI solutions across Reddit's business and technical functions.
Build AI applications, agents, and automations that solve real business problems.
Mentor engineers and set technical direction for AI-native workflows.
Reddit is a community of communities, hosting open and authentic conversations on the internet. With 100,000+ active communities and approximately 130 million daily active unique visitors, it is one of the internet's largest sources of information.