# Harnham — Machine Learning Engineering Manager

- Generated: 2026-09-08 02:08:48 PM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4464380161/
- Provider: LinkedIn
- Posted: approximately 2026-09-07 02:08 PM EDT (from '1 day ago')
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp
- Applicants: 95 applicants
- Work model/location: Remote — United States
- Compensation: $200,000-$230,000 plus bonus and equity
- Travel: Not disclosed
- Positioning track: Technical manager
- Fit outcome: FAIL — 86%

## Direct-match strengths

Production ML, Python, SQL, Spark, distributed systems, evaluation, pipelines, monitoring, and 5-10 person team leadership.

## Hard or material gaps

Hard applicant-count failure: LinkedIn displays 95 applicants, exceeding Keith's maximum of 89. The role also carries down-level risk relative to Keith's recent executive scope.

## Evidence map

1. Production ML (weight 3, evidence 3/3) — Direct.
2. Python/SQL/Spark (weight 3, evidence 3/3) — Direct.
3. Evaluation/monitoring (weight 3, evidence 3/3) — Direct.
4. Lead 5-10 (weight 2, evidence 3/3) — Direct.
5. Applicant ceiling (weight 3, evidence 0/3) — 95 applicants exceeds the maximum of 89.

## Full normalized job description

Machine Learning Engineering Manager
USA | Remote | $200,000 - $230,000 base + bonus + equity
A high-impact Machine Learning Engineering role focused on building and scaling production systems for real-time decisioning. You will manage a team of 5-10 and own end-to-end ML pipelines, working on models that directly drive commercial outcomes at scale, as well as contribute to ML research within the AI Lab.
The Company
They are a fast-growing technology business operating in the e-commerce and payments space, processing large volumes of real-time transactions. Machine learning sits at the core of their product, with strong investment in infrastructure and experimentation. Teams own services end to end, enabling engineers to drive meaningful technical impact.
The Role
• Build and deploy production-grade ML models for real-time systems
• Design scalable ML pipelines and infrastructure for high-throughput environments
• Develop offline experimentation and evaluation frameworks
• Improve model performance through statistical methods and feature engineering
• Work with distributed systems and large-scale data processing
• Partner with cross-functional teams to deliver ML solutions aligned to business needs
• Own the full lifecycle from experimentation to production and monitoring
Your Skills & Experience
• Strong commercial experience in Machine Learning Engineering
• Expertise in Python, SQL, and distributed frameworks such as Spark
• Deep understanding of model evaluation, experimentation, and statistics
• Experience building scalable ML systems from first principles
• Team leadership experience
What They Offer
• $200,000 - $230,000 base salary + bonus + equity
• Fully remote working in the US
• Unlimited paid time off and flexible working
• Comprehensive health and financial benefits, including 401k
• Learning budget and clear ownership of high-impact systems
How to Apply
Apply now to explore this Machine Learning Engineering opportunity.

## Artifact metadata

- Resume: Not generated because the fit gate returned FAIL.
- Cover letter: Not generated because the fit gate returned FAIL.
- LinkedIn note: Not generated for a FAIL role.
- Google Drive used: No