ML Engineering Manager

Harnham; New York (NY); Remote; USD 200,000 - 245,000; Full time

Benefits offered by this job

Annual bonus (up to 10%)

Unlimited PTO

401k match

12 weeks paid parental leave

Learning budget

Job summary

Harnham is seeking an ML Engineering Manager for Fraud and Risk to lead a team of engineers in building scalable ML models for e-commerce fraud decisions. This remote US role emphasizes experiments, rigorous evaluation, and close collaboration with risk and engineering leadership.

You will guide 4–7 ICs, drive hypothesis evaluation, and balance continuous improvement with research bets while ensuring models perform well in production environments.

Qualifications

• 5+ years in ML, data science or ML-adjacent software engineering.
• At least two years of people management, ideally three or more.
• Genuine depth in engineering or applied statistics, with real working competence in the other.

Responsibilities

• Lead and grow a team of 4 to 7 through 1:1s, career development and hiring.
• Partner with tech leads to decide which hypotheses get resourced, iterated or closed.
• Balance annual improvement targets with research bets and re-prioritisation as evidence arrives.
• Ensure offline results hold up online and across rolling windows.
• Converge experiments into release candidates and ship on a regular cadence.
• Collaborate with Risk as the primary stakeholder and present results to engineering leadership.

Skills

ML

Data science

People management

Quantitative targets

Education

PhD or Master’s in CS or Statistics

Job description

ML Engineering Manager, Fraud and Risk | Remote, US | $200,000 to $245,000 base + bonus

Lead a team of ML engineers whose models decide e-commerce transactions at scale, running a portfolio of experiments rather than a delivery queue.

The Company

An AI-driven fraud prevention platform that financially guarantees approved e-commerce orders. Its AI lab builds the ML products behind every fraud and risk decision, splitting effort between continuous model improvement and longer-horizon research bets.

The Role

• Lead and grow a team of 4 to 7 through 1:1s, career development and hiring.
• Partner with tech leads to decide which hypotheses get resourced, iterated or closed.
• Balance a committed annual improvement target against research bets, re-prioritising as evidence arrives.
• Bring rigour to evaluation, ensuring offline results hold up online and across rolling windows.
• Converge experimental workstreams into release candidates and ship on a regular cadence.
• Work with Risk as your primary stakeholder, and present results to engineering leadership and the wider company.

What We're Looking For

• 5+ years in ML, data science or ML-adjacent software engineering.
• At least two years of people management, ideally three or more. This is a hands-on player-coach role suited to a current team lead or first-line manager.
• Genuine depth in engineering or applied statistics, with real working competence in the other.
• Experience owning quantitative targets and structuring the work of strong individual contributors.
• Nice to have: a PhD or Master's in CS or Statistics, a risk or quantitative background, and payments or fraud experience.

What's On Offer

• Base of $200,000 to $245,000 depending on location, plus up to 10% annual bonus. Equity: [TBC].
• Remote from anywhere in the US, with an Eastern time zone preference and in-person time once a year.
• High autonomy, with direction set by data rather than a product backlog.
• Unlimited PTO, 401k match, 12 weeks' paid parental leave and a learning budget.
• US citizens and green card holders only. Visa sponsorship is not available.