# Harnham — ML Engineering Manager

- Generated: 2026-08-28 12:25:36 PM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4460128621/
- Posted: 26 minutes ago at capture time
- Applicants: Be among the first 25 applicants
- Work model/location: Fully remote — United States
- Employment type: Full-time
- Compensation: $200,000-$240,000 base plus annual performance bonus
- Travel: Not disclosed
- Positioning track: Technical manager
- Fit outcome: PASS — 94%

## Direct-match strengths

Near-exact team-size leadership, hands-on production ML, Python, SQL, Spark, experimentation, business KPIs, stakeholder communication, hiring, coaching, and research-to-production delivery are direct strengths.

## Hard or material gaps

Fraud, risk, payments, fintech, and decision science are preferred rather than required and are not claimed. Formal experimentation-framework depth is less explicit than Keith's production ML, forecasting, evaluation, and optimization record. The client is undisclosed in this recruiter listing.

## Weighted evidence map

1. Five-plus years in ML/applied science — 3/3: Direct long-running ML, predictive analytics, NLP, forecasting, and production AI evidence.
2. People management of technical teams — 3/3: Direct teams of seven, 11, 24, and 25 with hiring and development.
3. ML, statistics, and experimentation — 2/3: Direct ML and evaluation evidence; formal experimentation-framework ownership is less explicit.
4. KPI and business-outcome ownership — 3/3: Direct 50x, 60x, 90%, and rapid-release outcomes.
5. End-to-end production ML delivery — 3/3: Direct strategy, architecture, implementation, deployment, and operations.
6. Hands-on player-coach leadership — 3/3: Direct architecture, code, reviews, mentoring, and delivery leadership.
7. Python, SQL, Spark, and data platforms — 3/3: Direct source-supported evidence.
8. Large-scale production ML systems — 2/3: Strong enterprise and production evidence; exact current client scale is undisclosed.

## Full normalized job description

Machine Learning Engineering Manager
Location:
Fully Remote - based anywhere in the U.S.
Compensation:
$200-240k base, depending on location
A leading AI-driven technology company is seeking a Machine Learning Engineering Manager to lead a team developing and scaling production machine learning solutions that directly impact core business outcomes.
This is a player-coach leadership role suited to someone who combines strong technical depth with proven people management experience. You'll lead a team of 4-7 ML engineers and scientists, drive experimentation strategy, and help translate research into production results.
What You'll Do
Manage, mentor, and grow a team of 4-7 machine learning professionals.
Lead performance management, career development, hiring, and team culture initiatives.
Oversee a portfolio of ML experiments, balancing short-term business objectives with longer-term research opportunities.
Partner with technical leads and cross-functional stakeholders to prioritize initiatives and validate results.
Drive end-to-end delivery of machine learning solutions from experimentation through production deployment.
Communicate outcomes, insights, and priorities to technical and business audiences.
Required Qualifications
5+ years of experience in Machine Learning, Applied Science, or a related quantitative discipline.
2-3+ years of people management experience leading technical teams.
Strong background in machine learning, statistics, and experimentation.
Experience owning measurable KPIs, performance targets, or business outcomes.
Excellent communication and stakeholder management skills.
Hands-on technical leader who remains close to the work and enjoys coaching teams.
Preferred Qualifications
PhD or Master's in Computer Science, Statistics, Machine Learning, Mathematics, or a related field.
Experience in fraud, risk, payments, fintech, or decision science environments.
Exposure to large-scale production ML systems.
Tech Stack
Python, SQL, Spark, large-scale data platforms, experimentation frameworks, and production ML pipelines.
Benefits
Annual performance bonus
Unlimited PTO
401(k) match
Comprehensive medical, dental, and vision coverage
Paid parental leave
Professional development budget

## Artifact metadata

- Resume: https://bit.ly/4qKxBiu
- Cover letter: https://bit.ly/4cj4KvD
- Validation: PASS — 2-page resume (951 words), 1-page cover letter (224 words); geometry, annotations, bounds, text extraction, and links verified.
- Google Drive used: No