Machine Learning Engineer
US - California - Thousand Oaks - Field/Remote, United States
R
USD 129K-175K Mid-level Full Time
Tasks
- Apply AI and MLOps best practices with CI/CD
- Build scalable machine learning platforms
- Build traceability and reproducibility systems
- Collaborate to transition experiments to production solutions
- Create model training evaluation and deployment pipelines
- Deliver training content for model lifecycle management
- Develop containerized production MLOps solutions on cloud
- Develop machine learning workflows for model build deploy and manage
- Implement data pipelines and feature engineering workflows
- Monitor model performance and evaluations
- Productionize AI and ML solutions for drug discovery
- Set up experiment tracking and model registry systems
- Use infrastructure as code for reproducible deployments
Perks/Benefits
- Career development opportunities
- Comprehensive employee benefits
- Discretionary bonus
- Flexible spending accounts
- Flexible work models
- Life and disability insurance
- Remote work option
- Retirement and savings plan
- Stock-based long-term incentives
- Time off plans
Skills/Tech-stack
AWS | Apache Spark | CI/CD | Databricks | Docker | Experiment tracking | Feature Engineering | Kubeflow | Kubernetes | Langchain | MLOps | MLflow | Model Monitoring | Model Registry | PyTorch | Python | Scikit-learn | TensorFlow | Terraform | Test-Driven | Test-Driven Development | Version control | Weights and Biases
Education
Associate Degree | Bachelor of Science | High School Diploma | Master of Science
Regions
Countries
States
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