Career Category

Engineering

Job Description

As a Machine Learning Engineer at Amgen, you will be responsible for developing and optimizing the company's ML pipelines and architecture. You will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines.

The ideal candidate possesses a strong blend of technical expertise and data-driven problem-solving skills. As a Machine Learning Engineer, you will play a crucial role in designing, building, and optimizing our ML pipelines and platforms while mentoring junior engineers.

Roles & Responsibilities:

• Collaborate with data scientists to develop, train, and evaluate machine learning models.

• Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.

• Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.

• Implement best practices to automate ML workflows and improve efficiency.

• Conduct A/B testing and experimentation to optimize model performance.

• Work closely with data scientists, engineers, and product teams to deliver ML solutions.

• Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions.

• Take ownership of ML pipeline projects from inception to deployment, managing scope, timelines, and risks.

• Ensure data quality and integrity through rigorous testing and monitoring.

• Identify and resolve complex data-related challenges.

• Adhere to data engineering best practices and standards.

• Experience developing in an Agile development environment, and comfortable with Agile terminology and ceremonies.

• Familiarity with code versioning using GIT, Jenkins and code migration tools.

• Identifying and implementing opportunities for automation and CI/CD.

• Stay updated with the latest trends and advancements

Functional Skills:

Must-Have Skills (Not more than 3 to 4):

• Strong foundation in machine learning algorithms and techniques

• Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD)

• Proficiency in Python and relevant ML libraries (e.g., Tensor Flow, Py Torch, Scikit-learn)

• Outstanding analytical and problem-solving skills; Ability to learn quickly; Excellent communication and interpersonal skills

• Experience with data engineering and pipeline development

Good-to-Have Skills:

• Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification

• Knowledge of NLP techniques for text analysis and sentiment analysis

• Experience in analyzing time-series data for forecasting and trend analysis

• Experience with AWS, Azure, or Google Cloud

• Experience with Databricks platform for data analytics and MLOps

Professional Certifications (please mention if the certification is preferred or mandatory for the role):

• Any AWS Developer Certification(preferred)

• Any Python and ML certification (preferred)

• Databricks Certification (preferred)

• Any SAFe Agile certification (preferred)

Soft Skills:

• Initiative to explore alternate technology and approaches to solving problems.

• Skilled in breaking down problems, documenting problem statements, and estimating efforts.

• Effective communication and interpersonal skills to collaborate with cross-functional teams.

• Excellent analytical and troubleshooting skills.

• Strong verbal and written communication skills

• Ability to work effectively with global, virtual teams

• High degree of initiative and self-motivation.

• Ability to manage multiple priorities successfully.

• Team-oriented, with a focus on achieving team goals

• Strong presentation and public speaking skills.

Basic Qualifications:

• Master’s degree in computer science or STEM majors with a minimum of 5 years of Information Systems experience OR

• Bachelor’s degree in computer science or STEM majors with a minimum of 7 years of Information Systems experience.

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