Staff Machine Learning Engineer

Set the technical direction for ML, LLMs, and agents at Boam AI

Boam AI builds managed data solutions that transform messy, unstructured signals from public, private, and proprietary sources into structured, reliable, and always up-to-date intelligence on millions of SMBs and enterprises worldwide. These agentic systems power CRMs, data warehouses, AI products, and mission-critical decisions across the enterprise.

What You’ll Do

Set ML technical direction and roadmap: architecture, standards, and the next platform bets

Architect ML systems that blend classic models with LLM and agentic patterns

Own ML + agent workflows for entity resolution, attribute extraction, and verification

Build the shared pipelines and tooling that run those workflows at scale

Define standards for model training, deployment, and evaluation

Own reliability and quality metrics: evals, drift, and regressions

Lead technical design for ML-powered agents across multiple teams

Drive cross-functional technical decisions on ML tradeoffs: quality, cost, latency, reliability

Guide adoption of new ML and LLM research into production

Mentor ML engineers, including seniors, through feedback and design reviews

You Might Be a Fit If...

8+ years ML or AI engineering experience, including production ownership

Have architected LLM or agentic systems in real production environments

Strong Python skills and deep experience with ML infrastructure, pipelines, and evaluation

Comfortable designing high-throughput distributed ML systems and data flows

History of mentoring senior AI engineers and guiding their growth

Experience defining AI technical strategy and roadmaps for teams or orgs

Comfortable evaluating and introducing new ML tools, frameworks, and patterns

Bias to ship, measure, and refine while investing in key foundations

Motivated by hard real-world data problems and critical workflows

Why Boam AI

Join a no-politics, high-trust, low-ego, high-talent team

Own mission-critical ML and agent systems for enterprise customers

Work directly with founders, Head of Engineering, and engineering leaders

High autonomy, clear ownership, and visible impact from day one

Operate at the intersection of AI, data, and enterprise workflows

Top-tier compensation with meaningful equity participation

Help shape the ML platform, patterns, and culture of the company

Our Hiring Process Our process is fast, structured, and transparent – built to respect your time and surface real mutual fit

Intro Call

Brief call to meet and outline the role

Deep Dive

Review past ML and LLM systems and key decisions

Architecture + Leadership Exercise

Tackle a Boam-style ML and agent design problem

Founder Conversation

Align on values, ambition, and ownership expectations

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