Senior Machine Learning Engineer

Amgen • Thousand Oaks, CA

4d • Remote

About The Position

Join Amgen’s Mission of Serving Patients. At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Senior Machine Learning Engineer. What you will do. Let’s do this. Let’s change the world. In this vital role, you will contribute to the development of scalable machine learning platforms and workflows that enable scientists and researchers across Amgen to build, deploy, and manage AI/ML models. You will work closely with experienced engineers, data scientists, and domain experts to productionize machine learning solutions primarily in support of drug discovery and development. This is an ideal role for engineers early in their ML or software engineering careers who want to grow their expertise in MLOps, cloud platforms, and applied AI in life sciences. The ideal candidate has background in software engineering or computer science, has experience with commercial-grade, high reliability software and ML systems, and is passionate about the scientific and engineering aspects of designing new drugs. This role is eligible for remote in the US.

Requirements

• Doctorate degree OR Master’s degree and 2 years of relevant experience in Computer Science, IT, or related field OR Bachelor’s degree and 4 years of relevant experience in Computer Science, IT, or related field OR Associate’s degree and 8 years of relevant experience in Computer Science, IT, or related field OR 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.

Nice To Haves

• 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.
• Excellent critical-thinking and problem-solving skills.
• Strong communication and collaboration skills.
• Demonstrated presentation skills.
• Self-motivated, independent ownership and leadership skills.

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.

Benefits

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
• A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models where possible.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree