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