# Harnham — Manager of Machine Learning

- Generated: 2026-08-31 09:36:53 PM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4461205841/
- User-provided LinkedIn posting: https://www.linkedin.com/jobs/view/4461205841/
- Posting time: approximately 2026-08-31 11:36 AM EDT (estimated from LinkedIn's '10 hours ago')
- Applicants: 25 applicants
- Work model/location: Fully remote within the United States; four-day work week
- Employment type: Full-time
- Compensation: Up to $245,000 base plus bonus and equity
- Travel: Not disclosed
- Positioning track: Technical manager
- Fit outcome: PASS — 90%

## Direct-match strengths

Direct people leadership, hands-on ML/AI engineering, production systems, forecasting, model lifecycle and governance, player-coach delivery, ambiguity management, and stakeholder communication.

## Hard or material gaps

Formal experimentation-framework ownership is less explicit than Keith's direct model evaluation, forecasting, optimization, and production-platform evidence. The Manager title creates some overqualification risk, addressed through technical-manager positioning and hands-on operating motivation.

## Evidence map

1. ML and production AI systems — direct SageMaker, TensorFlow, forecasting, optimization, agentic AI, and production-platform evidence.
2. People management — direct hiring, coaching, reviews, and delivery accountability for teams of 7, 11, and 24.
3. Player-coach technical depth — direct Python, AWS, architecture, APIs, cloud deployment, model governance, and hands-on platform development.
4. Ambiguous and complex initiatives — direct founder, startup, transformation, and enterprise-advisory evidence.
5. Stakeholder communication — direct product, business, executive, and 200+ AWS customer engagements.
6. Experimentation frameworks — adjacent through model evaluation, hackathons, ML lifecycle, and iterative product validation rather than a named experimentation platform.

## Full normalized job description

ML Engineering Manager
Fully Remote (U.S.) | 4-Day Work Week (No Fridays)
Up to $245K Base + Bonus + Equity
U.S. Citizen or Green Card Required
We're partnering with an innovative, AI-driven company seeking a hands-on ML Engineering Manager to lead a team focused on building and deploying machine learning models at scale.
What You'll Do:
Lead and mentor a high-performing team of ML Engineers and Applied Scientists
Drive the development of production machine learning systems and experimentation frameworks
Balance near-term delivery goals with longer-term innovation initiatives
Partner with technical and business stakeholders to turn data-driven insights into impact
Stay close to the technology as a true player-coach while growing and developing your team
What We're Looking For:
5+ years of ML, Data Science, or ML-focused Software Engineering experience
3+ years of people management experience
Strong background in machine learning, experimentation, and production systems
Proven ability to lead teams through ambiguity and complex technical challenges
Excellent communication and stakeholder management skills
This is a rare opportunity to join a highly technical organization solving complex problems with AI while enjoying a true work-life balance through a four-day work week.
Reach out for more details. Confidential search.

## Artifact metadata

- Resume: https://bit.ly/3UqTsPX
- Cover letter: https://bit.ly/4qX4RDd
- Direct resume: https://files.keithsteward.com/Harnham/Keith_Steward_Machine_Learning_Engineering_Manager_4461205841_Resume.pdf
- Direct cover letter: https://files.keithsteward.com/Harnham/Keith_Steward_Machine_Learning_Engineering_Manager_4461205841_Cover_Letter.pdf
- Validation: PASS — 2-page resume (909 words), 1-page cover letter (220 words); PDF geometry, annotations, bounds, text extraction, and links verified.
- Archived JD capture: https://files.keithsteward.com/Harnham/Keith_Steward_Machine_Learning_Engineering_Manager_4461205841_JD_capture.md
- Google Drive used: No