Overview
ABOUT THE ROLE
Full job description
ABOUT THE ROLE You will build and deploy ML systems that power a core product in a fast moving startup environment. You will work across the full ML lifecycle from problem definition through production monitoring, collaborating with product and engineering teams to ship models that drive business impact. WHAT YOU'LL DO
- Design, train, and evaluate machine learning models for production use cases.
- Implement end to end ML pipelines from data preprocessing to model serving and monitoring.
- Translate business requirements into ML solutions in collaboration with cross functional teams.
- Debug and optimize model performance in production and iterate based on real world feedback.
- Write clean, maintainable code and contribute to ML infrastructure and tooling.
- Participate in code reviews and share knowledge with the broader team. WHAT WE'RE LOOKING FOR
- 3+ years of professional experience in machine learning or software engineering with hands on applied ML work in production systems.
- Strong fundamentals in model selection, feature engineering, evaluation and validation.
- Proficiency in Python for ML development and experience with ML frameworks such as TensorFlow, PyTorch, or scikit learn.
- Experience building, deploying, and maintaining ML systems at scale including data pipelines, monitoring, A/B testing and MLOps tools (for example cloud ML platforms, Kubernetes, Docker).
- Experience implementing end to end ML pipelines and deploying ML systems in production with experimentation frameworks.
- Ability to work in a fast moving product environment with rapid iteration and ambiguity. COMPENSATION & BENEFITS Compensation details are provided by the employer upon request. LOCATION On site in San Francisco, California, United States
Tips for this job
Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Verification notes
laptop-ats-crawler v3
Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
Clera (ashby) ↗Browse current Job and Scholarship listings from Clera (ashby) →