Senior Manager, Machine Learning Platform Engineer

Scorpion Therapeutics; United States; On-site; USD 158,000 - 204,000; Full time

Benefits offered by this job

Bonus/Stock incentives

Paid time off

Medical/dental/vision/life insurance

Job summary

Scorpion Therapeutics is seeking a highly capable ML/Data Engineer to drive end-to-end initiatives, from problem framing to production. You will self-direct projects, automate cloud infrastructure with IaC and containers, and build pipelines that move models from experimentation to serving in QMS contexts.

The role requires strong Python/SQL skills, experience with AWS/Azure, and ability to ensure governance, security, and quality in GxP environments; collaboration across teams is essential.

Qualifications

• BS with 8+ years, MS with 6+ years, or PhD/PharmD required.
• Proven experience in end-to-end ML lifecycle and production systems.
• Strong skills in Python, SQL, and modern ML frameworks.

Responsibilities

• Operate as a self-directed ML/Data engineering contributor across end-to-end initiatives.
• Automate cloud infra using IaC and containers for reproducible experiments.
• Manage ML lifecycle from experimentation to production and support deployment.
• Build data pipelines across QMS sources.
• Orchestrate workflows with logging, retries, and SLAs.
• Monitor model performance and data quality.
• Collaborate cross-functionally and ensure security and governance in GxP environments.

Skills

Python

SQL

Git

CI/CD

AWS/Azure

Docker/Kubernetes

Databricks

Model evaluation

Bias avoidance

Communication

Education

BS + 8 years OR MS + 6 years OR PhD/PharmD

Tools

Terraform

scikit-learn

PyTorch

TensorFlow

XGBoost

Datadog

Prometheus

CloudWatch

Job description

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.
• Company-sponsored medical/dental/vision/life insurance.