Design, build, and deploy production-grade machine learning models and systems at scale
Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
Build scalable data and model pipelines with strong reliability, observability, and automated retraining
Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.
Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
Improve system performance across latency, throughput, and model quality metrics
Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment
Contribute to technical strategy, architecture, and long-term ML roadmap

Requirements

3-5+ years of experience building, deploying, and operating machine learning systems in production
Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
Experience improving measurable metrics through applied machine learning.

Benefits

Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningfeature engineeringmodel evaluationmodel deploymentmodel monitoringdata pipelinesXGBoostRandom Forestsdeep learningtransformers

Soft Skills

cross-functional collaborationproblem-solvingcommunicationtechnical strategyarchitecture design