# Senior Engineering Manager, ML Platform - Company: [Sift]() - Location: Remote - USA · Seattle, Washington · San Francisco, California - Remote: Yes - Team: Engineering - Employment type: Full Time - Salary: $240K – $340K - Posted: August 26, 2026 ## Job description **Location:** San Francisco, California or Seattle, Washington **Employment Type:** Full time **Location Type:** Hybrid **Department:** Engineering ## About the Team The Machine Learning Platform team — internally known as "Potato Radius" — builds the training pipelines, feature infrastructure, and evaluation systems behind every score Sift returns, across more than 700 customers and a trillion-plus events a year. We give Sift's Data Science and ML Engineering teams the tooling to ship models fast, prove they work, and trust them in production. ## What We're Looking For We're hiring a Senior Engineering Manager to lead this team as a backfill for our outgoing lead. This isn't a maintenance role — it's a chance to modernize a foundational platform at a moment when the stakes are high: our biggest deals increasingly come down to who can win a competitive proof-of-value the fastest, and this team's tooling determines whether we win it. You're a manager who's inspiring and technical, and who knows how to bring focus to what matters now without losing sight of the long term. You value collaboration and transparency, operate with a get-stuff-done mindset, and bring the technical depth and bias for shipping to spot the manual, brittle, or duplicated work that's quietly slowing the team down. You build a culture of mentorship, give regular and constructive feedback, set clear goals, and grow your team by hiring effectively. ## Projects You Might Lead * Launch a unified model evaluation framework that gives Data Science fast, trustworthy, apples-to-apples comparisons before a model ever reaches production or shadow traffic. * Evolve core feature infrastructure — including a new global feature store — to improve accuracy and unlock faster experimentation. * Build the tooling and metrics that let Sift run faster, sharper customer proof-of-value engagements, online and offline, so we win competitive bake-offs instead of losing them to slow iteration. * Bring a fresh approach to model configuration, replacing tribal knowledge and manual gating with auditable, safely-controlled releases. * Introduce agentic, AI-assisted tooling into customer investigations, automating repetitive data pulls and validation so analysts spend their time on judgment calls, not manual digging. * Build automation that detects an active fraud attack, adjusts score calibration in real time, and cleanly reverts once it subsides. ## What You'll Do * **Lead and grow the team:** Own the roadmap, execution, and quality of the systems that train, evaluate, and serve Sift's ML models in production, leading a team of ML platform engineers and data scientists. * **Stay technical:** Review designs, unblock engineers on hard problems, and make credible calls on architecture and trade-offs. * **Drive customer POVs:** Partner directly with strategic customers and Sales/Solutions Engineering on technical proof-of-value engagements, translating customer requirements into platform capabilities. * **Reduce technical debt:** Drive a sustained, measurable reduction in technical debt across the ML platform, balancing new feature delivery with the health of existing systems. * **Build evaluation frameworks:** Mature the systems that give Data Science and ML Engineering fast, trustworthy signals on model quality before and after deployment. * **Automate the ML lifecycle:** Identify repeatable, manual processes across training, evaluation, deployment, and monitoring, and drive their automation. * **Partner cross-functionally:** Align platform investments with business priorities alongside Data Science, Core Infrastructure, Product, and Customer Success. ## Technical Stack GCP, AWS, Spark, Kafka, Kubernetes, Docker, Databricks, Python ## What Would Make You a Strong Fit * 8+ years of overall hands-on engineering experience, including 4+ years managing software or machine learning engineering teams. * Deep technical fluency in machine learning systems: model training pipelines, feature engineering, model serving, and evaluation at production scale. * Proven track record leading technical customer engagements or POVs, including direct interaction with enterprise customers. * Demonstrated success reducing technical debt in a live, high-traffic production system without stalling feature delivery. * Experience designing or scaling evaluation frameworks (offline and/or online) for machine learning models. * Track record of identifying manual, repeatable engineering processes and driving their automation. * Experience hiring, mentoring, and developing engineering talent. * B.S. in Computer Science (or related technical discipline), or equivalent practical experience. ## Bonus Points * Experience with large-scale distributed ML infrastructure such as Spark, Flink, Databricks, or similar. * Familiarity with fraud detection, risk, or trust & safety domains. * Hands-on experience with GCP or AWS ML infrastructure. * Experience with streaming architectures (e.g., Kafka) and containerized/orchestrated deployments (Docker, Kubernetes). * Familiarity with using AI coding assistants (e.g., Claude Code) to accelerate development. ## Our Interview Process * **Introduction interview:** 30- 45 minutes with a recruiter to discuss your background and the role. * **Hiring Manager interview:** 30- 45 minutes with the hiring manager to explore your fit for the position. * **Hybrid onsite loop with the team:** approximately 4–5 hours covering system design, a technical deep dive, a cross-functional stakeholder scenario, and values & behavior. ## Benefits and Perks * Competitive total compensation package * 401k plan * Medical, dental and vision coverage * Wellness reimbursement * Education reimbursement * Flexible time off **Let’s build it together:** At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet. *This document provides transparency around how Sift handles the personal data of job applicants:* [*https://sift.com/recruitment-privacy*](https://sift.com/recruitment-privacy) **A little about us:** Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at [sift.com](http://sift.com) and follow us on [LinkedIn](https://www.globenewswire.com/Tracker?data=XHeK0v8NcNrEkwcDe8QxwpZeCkdQqNyKlni83U-CUmrprdKXWpVlYOAbVzwe2OmlwIUN-q4HXk4hf_dazpHx2NMM1CW_SYj740q9mxXNQI4=). ## Apply [Apply on Sift]() Canonical job page: