Sr Machine Learning Engineer

Amgen • Thousand Oaks, CA

3h • Hybrid

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. 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.

Requirements

• Bachelor’s degree (or foreign equivalent) in Computer Science, Statistics, Electrical Engineering, Mathematics, Bioengineering or a related field and 4 years of experience in the job offered or in a Data Scientist related – Occupation
• 4 years of experience in Programming skills in Python including experience with scientific computing and machine learning libraries including pandas, NumPy, scikit-learn, XGBoost, LightGBM, TensorFlow and PyTorch
• 4 years of experience in Applying supervised and unsupervised learning techniques to real-world problems, including experience with Random Forest, XGBoost, ensemble models, and deep learning architectures
• 4 years of experience in Version control (Git), containerization and orchestration tools including Docker and Kubernetes, and cloud environments including AWS or GCP
• 4 years of experience in Involved with data science platforms including Databricks and SageMaker
• 4 years of experience in Using statistical methods industry including regression modeling, hypothesis testing, Bayesian methods, Forecasting techniques and time-series analysis
• 4 years of experience in Building ETL (Extract, Transform, Load) pipelines for handling large-scale, high-dimensional datasets, familiarity with healthcare data structures and data types
• 4 years of experience with software DevOps CI/CD tools and GitLab
• 4 years of experience developing and fine-tuning Natural Language Processing (NLP) models, including work with architectures such as BERT, ALBERT, GPT, and other transformer-based models

Responsibilities

• Lead efforts with Amgen business leaders to identify, explore and develop transformative AI and ML solutions to enable access to computational tools and data within Amgen, and ultimately improve patient outcomes across multiple therapeutic areas
• Utilize Cloud Services to collect, store, preprocess, and analyze large datasets from various sources across Amgen
• Collaborate with other ML engineers, data scientists and research scientists to identify appropriate ML models and algorithms
• Facilitate ML & Data engineering efforts by architecting and guiding the implementation of data and ML pipelines for development and deployment
• Facilitate model deployment to production, including monitoring and maintenance of ML models, put in place metrics to assess accuracy and drift
• Define model evaluation and validation strategies, train and test models, and analyze and resolve errors and biases in models
• Lead and develop standards, processes, and best practices for the team across the machine learning-based solution implementation lifecycle
• Involved in technical guide and career development mentor to junior machine learning engineers and data scientists in a formal or matrixed fashion

Benefits

• stock
• retirement
• medical
• life and disability insurance
• eligibility for an annual bonus
• health and welfare plans for staff and eligible dependents
• financial plans with opportunities to save towards retirement or other goals
• work/life balance
• career development opportunities
• Retirement and Savings Plan with generous company contributions
• group medical, dental and vision coverage
• flexible spending accounts
• discretionary annual bonus program
• sales-based incentive plan
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models, including remote and hybrid work arrangements, where possible

What This Job Offers

• Job Type: Full-time
• Career Level: Senior