DeepRec.ai is hiring: Machine Learning Engineer in New York

DeepRec.AI is partnered with a well‑funded, high‑growth AI company building real‑world autonomous systems in a complex, high‑stakes domain.

You’ll own end‑to‑end ML systems in production, designing, experimenting, and shipping agents that actually do meaningful work.

What makes this role different?

You’ll operate at the intersection of:

• LLMs / agent systems


• Product + infrastructure


• Research + engineering

Designing systems that reason, plan, evaluate themselves, and improve over time, not just single-model pipelines.

What you’ll be doing:

Build agent systems

• Design and iterate multi-agent architectures


• Define tool use, autonomy boundaries, and fallback logic


• Manage context, memory, and long-running workflows


• Optimize across latency, cost, and performance

Own evaluation + experimentation:

• Build scalable eval frameworks (offline + online)


• Define metrics, golden datasets, and feedback loops


• Track failures, regressions, and error taxonomies


• Use data to drive product and architecture decisions

Work deeply on retrieval + reasoning:

• Design prompt stacks and structured reasoning flows


• Build retrieval/indexing pipelines


• Turn messy, real‑world data into structured inputs for agents


• Implement guardrails for reliability + safety


• Scope problems from first principles


• Ship production systems, not prototypes


• Act as a true owner: build, measure, iterate

Ideal background:

• 3–10 years building data-heavy or ML-driven products


• Strong Python + systems thinking


• Experience with at least one of:


• LLMs / agent frameworks


• Search / retrieval / ranking systems


• Complex backend or data infrastructure

Why this role?

• Real impact: systems already used in production today


• High ownership: you ship what you build


• Tight feedback loops: fast iteration, real learning