9 часов назад
Staff Machine Learning Engineer - Retention
170 000 - 225 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff Machine Learning Engineer - Retention (Machine Learning/Ranking): Building and operating production machine learning systems that improve repeat purchases, customer lifetime value, matching, recommendations, pricing, and retention at a marketplace scale with an accent on end-to-end model ownership and reliable ML infrastructure. Focus on ranking and recommender systems, scalable feature pipelines, real-time and batch deployment, model monitoring, and solving complex marketplace optimization problems.
Location: Hybrid, requiring two days per week in the San Francisco or New York City office every Tuesday and Wednesday
Salary: $170,000–$225,000 base pay annually
Company
is a marketplace platform connecting customers with Taskers for home services such as furniture assembly, handyman work, and moving assistance.
What you will do
- Own the reliability and performance of the tasker-to-job ranking system and improve First-Time Right rates.
- Build machine learning solutions for repeat purchases, personalized recommendations, category discovery, dynamic pricing, and customer retention.
- Manage the full model lifecycle from feature engineering and training through evaluation, deployment, monitoring, and production optimization.
- Build scalable ML infrastructure and data pipelines for real-time, near-real-time, and batch workloads.
- Develop monitoring and observability systems for data quality and model performance.
- Write maintainable production code and contribute to reviews, documentation, and engineering best practices.
Requirements
- 8+ years of industry experience building and deploying production-grade machine learning models and systems.
- Strong experience with machine learning for search, ranking, recommender systems, pricing and elasticity modeling, or predictive analytics.
- Proficiency in Python or another programming language, SQL, and popular machine learning libraries such as Scikit-learn, LightGBM, XGBoost, TensorFlow, or PyTorch.
- Experience building REST API services and working with Docker, Kubernetes, Kafka, Airflow, data warehouses, and data lakes.
- Experience with model deployment, monitoring, data quality, and scalable feature engineering.
- BS, MS, or PhD in computer science, statistics, operations research, or a related quantitative field.
Nice to have
- Experience with dbt, infrastructure as code, GitHub Actions, and CI/CD pipelines.
- Experience working in marketplace or platform environments involving ranking, matching, and pricing.
Culture & Benefits
- Hybrid work model with regular in-person collaboration.
- Employer-paid health insurance and a 401(k) match with immediate vesting for US-based employees.
- Flexible paid time off and two company-wide closure weeks.
- Product, wellness, productivity, and education stipends.
- IKEA discounts and reproductive health support.
- Benefits vary by country of employment.
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