Senior Manager, Machine Learning Platform Engineer
Gilead Sciences
August 10, 2026
Remote friendly (San Francisco Bay Area)
United States
IT
Primary Responsibilities
- Operate as a self-directed ML/Data engineering contributor: scope, plan, and drive end-to-end initiatives translating quality problems into production solutions.
- Automate cloud infrastructure and environments using infrastructure-as-code and containers; enable reproducible training/serving/experimentation.
- Manage the full ML lifecycle: build pipelines to move models from experimentation to production (packaging, CI/CD, testing, deployment) and support serving for signal detection, risk analytics, and Quality Performance/Quality Health.
- Build batch/streaming data pipelines across QMS sources (Audit, Deviation, CAPA, Risk Management); define feature sets, lineage, and reuse.
- Orchestrate and operate observable workflows (retries, dependencies, SLAs) and implement logging/tracing/alerting.
- Monitor model performance, data drift/bias, service health, and data quality.
- Support AI/agent workflow exploration with clear human/automation boundaries; design prompts/instructions and manage AI context/cost.
- Collaborate cross-functionally; set up validation/testing (type checks, linting, integration/contract tests); maintain documentation/runbooks and ensure security/access/data governance for GxP-regulated environments.
Qualifications
- BS + 8 years OR MS + 6 years OR PhD/PharmD.
Preferred / Required Skills
- Python and SQL; Git; CI/CD (e.g., GitHub Actions); AWS or Azure; Docker/Kubernetes; Databricks; model evaluation/scoring and bias avoidance.
- Preferred: Terraform; scikit-learn, PyTorch, TensorFlow, XGBoost; monitoring tools (Datadog/Splunk/CloudWatch/Prometheus); distributed computing; troubleshooting; strong communication.
- People leadership accountabilities: create inclusion, develop talent, empower teams.
Compensation/Benefits
- Salary range: $157,590–$203,940. May be eligible for bonus/stock incentives, paid time off, and company-sponsored medical/dental/vision/life insurance.
Application Instructions
- Apply via the Internal Career Opportunities portal in Workday.
- Operate as a self-directed ML/Data engineering contributor: scope, plan, and drive end-to-end initiatives translating quality problems into production solutions.
- Automate cloud infrastructure and environments using infrastructure-as-code and containers; enable reproducible training/serving/experimentation.
- Manage the full ML lifecycle: build pipelines to move models from experimentation to production (packaging, CI/CD, testing, deployment) and support serving for signal detection, risk analytics, and Quality Performance/Quality Health.
- Build batch/streaming data pipelines across QMS sources (Audit, Deviation, CAPA, Risk Management); define feature sets, lineage, and reuse.
- Orchestrate and operate observable workflows (retries, dependencies, SLAs) and implement logging/tracing/alerting.
- Monitor model performance, data drift/bias, service health, and data quality.
- Support AI/agent workflow exploration with clear human/automation boundaries; design prompts/instructions and manage AI context/cost.
- Collaborate cross-functionally; set up validation/testing (type checks, linting, integration/contract tests); maintain documentation/runbooks and ensure security/access/data governance for GxP-regulated environments.
Qualifications
- BS + 8 years OR MS + 6 years OR PhD/PharmD.
Preferred / Required Skills
- Python and SQL; Git; CI/CD (e.g., GitHub Actions); AWS or Azure; Docker/Kubernetes; Databricks; model evaluation/scoring and bias avoidance.
- Preferred: Terraform; scikit-learn, PyTorch, TensorFlow, XGBoost; monitoring tools (Datadog/Splunk/CloudWatch/Prometheus); distributed computing; troubleshooting; strong communication.
- People leadership accountabilities: create inclusion, develop talent, empower teams.
Compensation/Benefits
- Salary range: $157,590–$203,940. May be eligible for bonus/stock incentives, paid time off, and company-sponsored medical/dental/vision/life insurance.
Application Instructions
- Apply via the Internal Career Opportunities portal in Workday.