Senior Data Scientist, ML Systems & Production

Hims & Hers Health, Inc.; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Competitive pay

Unlimited PTO

Health benefits

ESPP

401k

Offsite retreats

Job summary

Hims & Hers Health, Inc. is seeking a senior ML Engineer/Architect to design and deploy automated ML systems at scale. You will balance pragmatic trade-offs while writing production code and shaping our core ML infrastructure.

You will translate business questions into actionable roadmaps, lead end-to-end deployment, and ensure robust integration with our production stack. Mentorship and cross-team collaboration are essential to drive measurable business impact.

Qualifications

• 8+ years in Data Science or ML Engineering with production systems impact.
• Strong Python and SQL; pandas/NumPy/scikit-learn expertise.
• Experience with PyTorch or XGBoost/LightGBM.
• Ability to design scalable, long-term ML solutions and systems.
• Proven leadership and ability to influence without authority.
• CI/CD and ML Ops in cloud production environments (AWS or GCP).

Responsibilities

• Architect the 0-to-1 ML foundation and automated systems.
• Translate ambiguous business questions into concrete technical roadmaps.
• Lead end-to-end deployment of ML products with robust production readiness.
• Partner across Engineering, Product, and Business to align technical and business goals.
• Define technical standards and lead design docs and peer reviews.
• Own the full model lifecycle from data design to long-term value.
• Mentor Senior and Mid-level Data Scientists to raise the technical bar.

Skills

Python

SQL

ML frameworks

Education

BS/MS/PhD in Quantitative Field

Tools

PyTorch

XGBoost/LightGBM

AWS/GCP

Job description

Hims & Hers Health, Inc. is seeking a senior ML Engineer/Architect to design and deploy automated ML systems at scale. You will balance pragmatic trade-offs while writing production code and shaping our core ML infrastructure.

You will translate business questions into actionable roadmaps, lead end-to-end deployment, and ensure robust integration with our production stack. Mentorship and cross-team collaboration are essential to drive measurable business impact.