Note: The job is a remote job and is open to candidates in USA. Amgen is a biotechnology company focused on developing medicines for serious illnesses. The Senior Machine Learning Engineer will help build scalable machine learning platforms and workflows, productionize AI/ML solutions for drug discovery and development, and support scientists in managing model lifecycles.
Responsibilities
- Deliver AI and ML-enabled applications and platforms, with deployed models ranging from classical ML models to natural language processing, protein language models, and large language models
- Contribute to the development and maintenance of ML platform capabilities, including: + Data pipelines and feature engineering workflows + Model training, evaluation, and deployment pipelines + Experiment tracking and model registry systems + Model performance evaluations and monitoring
- Partner in implementation of AI and ML Ops best practices, including CI/CD, cloud infra as code, monitoring, traceability and reproducibility
- Collaborate with cross-functional teams to transition standards and outcomes from experimentation to production-grade enterprise solutions
- Build and maintain scalable and efficient, productionized MLOps solutions on cloud platforms
- Develop and deliver training content and knowledge articles to educate resident scientists on model lifecycle management best practices
Skills
- Doctorate degree
- Master's degree and 2 years of relevant experience in Computer Science, IT, or related field
- Bachelor's degree and 4 years of relevant experience in Computer Science, IT, or related field
- Associate's degree and 8 years of relevant experience in Computer Science, IT, or related field
- High school diploma / GED and 10 years of relevant experience in Computer Science, IT, or related field
- Software programming (Python, version control, test driven development)
- Experience with cloud technologies (AWS preferred, Databricks)
- Hands-on experience with AI/ML model training and serving
- Excellent critical-thinking and problem-solving skills
- Strong communication and collaboration skills
- Demonstrated presentation skills
- Self-motivated, independent ownership and leadership skills
- Experience with deployment and maintenance of AI/ML models in production
- Substantial experience with cloud technologies and platforms, such as Databricks, AWS (preferred), or Azure
- Experience with AI and MLOps frameworks and tools (MLflow, Kubeflow, Weights & Biases, Terraform, etc.)
- Experience with containerization (Docker, Kubernetes)
- Familiarity with distributed data processing (e.g., Spark)
- Familiarity with data science libraries (scikit-learn, TensorFlow, PyTorch, LangChain)
- Experience with graph databases
Benefits
- Health and welfare plans for staff and eligible dependents
- Retirement and Savings Plan with generous company contributions
- Group medical, dental and vision coverage
- Life and disability insurance
- Flexible spending accounts
- A discretionary annual bonus program
- Stock-based long-term incentives
- Award-winning time-off plans
- Flexible work models where possible
- Career development opportunities
Company Overview
Company H1B Sponsorship