Senior Engineering Manager, ML Platform
$240k - $340k • Remote - USA • FullTime
Posted 1mo ago
Job Location
Remote - USA
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
Sift is seeking a Senior Engineering Manager to lead its Machine Learning team, internally known as "Potato Radius." This team is responsible for building and maintaining the training pipelines, feature infrastructure, and evaluation systems that power Sift's scoring across a massive scale of events and customers. The ideal candidate is an inspiring and technical manager who can balance immediate priorities with long-term vision, foster collaboration and transparency, and drive a get-stuff-done mindset. You will be instrumental in building a culture of mentorship, providing constructive feedback, setting clear goals, and growing the team through effective hiring.
Responsibilities
- Lead and grow the ML platform team, owning the roadmap, execution, and quality of ML model training, evaluation, and serving systems.
- Maintain technical depth by reviewing designs, unblocking engineers, and making architectural trade-off decisions.
- Partner with strategic customers, Sales, and Solutions Engineering on technical proof-of-value engagements, translating customer needs into platform capabilities.
- Drive a measurable reduction in technical debt across the ML platform, balancing new feature development with system health.
- Mature systems for providing Data Science and ML Engineering with fast, trustworthy model quality signals.
- Identify and automate repeatable, manual processes across the ML lifecycle (training, evaluation, deployment, monitoring).
- Align platform investments with business priorities by partnering cross-functionally with Data Science, Core Infrastructure, Product, and Customer Success.
Requirements
- 8+ years of overall hands-on engineering experience.
- 4+ years of experience managing software, data science, or machine learning engineering teams.
- Experience managing Data Scientists or in-depth knowledge of data science.
- Deep technical fluency in production-scale machine learning systems (model training pipelines, feature engineering, model serving, evaluation).
- Proven track record leading technical customer engagements or proof-of-value initiatives.
- Demonstrated success in reducing technical debt in a live, high-traffic production system without hindering feature delivery.
- Experience designing or scaling evaluation frameworks for machine learning models.
- Track record of identifying and automating manual, repeatable engineering processes.
- Experience hiring, mentoring, and developing engineering talent.
- B.S. or M.S./Ph.D. in Computer Science (or related technical discipline), or equivalent practical experience.
Benefits
- Competitive total compensation package
- 401k plan
- Medical, dental, and vision coverage
- Wellness reimbursement
- Education reimbursement
- Flexible time off