Latent AI

Compensation

Full Description

Who we're looking for We’re looking for an experienced, hands-on ML/AI engineer (typically 5+ years of relevant experience, or a PhD with equivalent expertise) to join our team building the next generation of tooling for ML/AI on the edge. What you’ll do Balance independence and collaboration: you make quick, informed decisions on your own, but stay aligned with the team and company goals. Value both agency and teamwork, and bring strong communication skills to keep collaboration productive. Enjoy supporting the growth of others: sharing knowledge, mentoring junior teammates, and helping the whole team level up. Extend our technology and products for edge MLOps: clean interfaces, reliable services, and ergonomics that make ML workflows fast and repeatable. Build products that enable users to explore, assess, and improve training data quality at scale (e.g. embeddings, clustering, distillation). Enhance automated MLOps pipelines with new models, optimization strategies, and evaluation methods to mine predictive signal from large experiment corpora. Help evolve our agentic layer so customers can interact with the system naturally (query state, orchestrate runs, interpret results). Ship production-grade code with strong CI/CD, tests, and docs; raise reliability and developer experience across the stack. How we decide An ideal candidate will be someone with; Technical depth in ML/AI with a preference for computer vision and NLP Proven contributions, whether in industry or academia, that moved innovative ideas closer to product. 2-3 years industry experience Hands-on execution: the ability to design, build, and ship, not just theorize. Collaborative independence: you’re comfortable making autonomous progress, but you thrive in a team environment. Growth mindset: curiosity, adaptability, and willingness to learn new approaches and tools. Are fluent in Python and modern ML frameworks like PyTorch; familiarity with agentic AI frameworks is a bonus. Know your way around CI/CD, automated testing, and documentation, and care about building robust systems. Have some familiarity with data science front-end/UI workflows to support quick demonstrations (streamlit, dash, gradio). Have a track record of driving innovation from research or prototypes into production ready features or products US citizenship preferred but not a requirement Candidates based in NJ, NY or Washington DC are preferred