Who we're looking for

We’re looking for an experienced, hands-on ML/AI engineer (typically 2-3 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 preferred, remote/hybrid possible