Manager of Machine Learning

Harnham; United States; On-site; USD 200,000 - 245,000; Full time

Benefits offered by this job

Unlimited PTO

401k match

Health/dental/vision

FSA

Life & disability insurance

Parental leave 12 weeks

Therapy benefit

Learnerbly learning budget

Light onsite once a year

Job summary

Harnham is hiring a hands-on ML engineering manager to lead a team of 4-7 engineers remotely across the United States. You will steer a portfolio of experiments, validate results rigorously, and balance near-term improvements with longer-horizon research bets. This is a technical leadership role with direct code involvement.

You will partner with Risk and engineering leadership, owning model performance while thresholds and rules are defined by Risk. Expect a high-impact, data-driven environment.

Qualifications

• 5+ years in ML, data science or ML-adjacent engineering.
• 3+ years of people management.
• Hands-on with code and evaluation pipelines; not a pure manager.
• Excellent written and verbal communication.

Responsibilities

• Lead and grow a team of 4-7 ML engineers: career development and hiring.
• Run a portfolio of experiments with roadmap partners and rigorous validation.
• Balance short-term improvements with longer-horizon research bets.
• Own delivery cadence and ship release candidates from experiments.
• Set direction with Risk; own model performance targets.
• Present results to engineering leadership and the wider company.

Skills

People management

Machine learning

Data science

Team leadership

Experimentation

Communication

Statistics

Software engineering

Education

Advanced degree in ML/CS

Tools

Python

Evaluation pipelines

ML platform

Job description

Remote, US | $200k-$245k (Base + Bonus + Equity), banded by location

You'll be a hands-on Player-Coach for a team of 4-7 ML engineers - running a portfolio of experiments, not a delivery queue. You stay close enough to the work to have a grounded technical opinion, while building the people, process, and rigor that turns hypotheses into shipped model improvements.

The Company

A fraud-prevention fintech protecting e-commerce checkout at scale - processing billions of transactions a year across 100+ countries for roughly 1,000 merchants. The product is structured as a guarantee: instead of merchants bearing fraud risk, the company takes it on, backed by real-time ML decisioning. Series E, ~500 employees, strong in-house ML platform and engineering rigor.

The Role

This is a genuinely technical management seat, not a process-and-politics role.

• Lead and grow a team of 4-7 ML engineers: career development, 1:1s, conflict management, hiring, and building a culture where negative results are treated as valid progress.
• Run a portfolio of experiments: partner with tech leads who own the roadmap, decide which hypotheses get resourced or killed, and bring rigor to validating results before they're called wins.
• Balance a committed yearly improvement target against longer-horizon research bets, re-cutting priorities as evidence arrives.
• Own delivery cadence: converge independent experimental workstreams into shippable release candidates, including the call to cut ones that aren't pulling their weight.
• Set direction from data in partnership with Risk, your primary stakeholder - you own model performance, they own thresholds and rules.
• Represent your team's results to engineering leadership, Risk, and the wider company.

What We're Looking For

• 5+ years in machine learning, data science, or ML-adjacent engineering, including 3+ years of people management.
• Genuine depth in engineering or applied statistics, with real working competence in the other — not a manager of analysts, and not a manager of a pure software team.
• Currently operating at Team Lead / Tech Lead level or an early-tenure manager, still hands-on with code and evaluation pipelines.
• Demonstrated ability to lead under real uncertainty — setting direction before the answer is known, and changing course when evidence says to.
• Excellent written and verbal communication; much of the decision-making here happens in documents.
• Comfort being given a quantitative target and figuring out how to hit it.
• A plus, not a requirement: payments or fraud domain experience.

What's On Offer

• Base $200k-$245k depending on location tier, plus up to 10% annual bonus and equity.
• Unlimited PTO, 401k match, health/dental/vision, FSA, life & disability insurance.
• 12-week paid parental leave, therapy benefit, Learnerbly learning budget.
• Fully remote across the US, with light onsite expectations (roughly once a year).