Amgen

Biotechnology

MachineLearningEngineer

India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Machine Learning Engineer at Amgen. Skills: Machine Learning, MLOps, Python, Cloud Platforms. Develop machine learning models. Train machine learning models”

What You'll Achieve.

Improve efficiency; Optimize model performance; Achieve team goals

Industry & Context.

Biotechnology
Problems you'll solve

Analytical and problem-solving skills; Troubleshooting skills

What They're Looking For.

Must Have

Machine learning algorithms and techniques, MLOps practices and tools, DevOps tools, Python, TensorFlow, PyTorch, Scikit-learn, Analytical and problem-solving skills, Ability to learn, Communication and interpersonal skills, Master’s degree with 5+ years of experience in Computer Science, IT or related field OR Bachelor’s degree with 7-9 + years of experience in Computer Science, IT or related field

Nice to Have

Big data technologies, Spark, Hadoop, Data engineering and pipeline development, Statistical techniques and hypothesis testing, Regression analysis, Clustering and classification, NLP techniques for text analysis and sentiment analysis, Analyzing time-series data for forecasting and trend analysis, Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.)

What You'll Do.

Develop machine learning models

Train machine learning models

Evaluate machine learning models

Build MLOps pipelines

Maintain MLOps pipelines

Leverage cloud platforms

Implement DevOps/MLOps best practices

Automate ML workflows

Develop monitoring systems

Perform experimentation

How You'll Work.

Team & Collaboration

Collaborate with data scientists; Work closely with data scientists; Work closely with engineers; Work closely with product teams; Work effectively with global, virtual teams

Communication Scope

Good communication skills; Interpersonal skills; Verbal communication skills; Written communication skills; Presentation skills; Public speaking skills

Process & Methodology

Ability to manage multiple priorities

Full Job Description

## **Career Category** Engineering ## ## **Job Description** **Machine Learning Engineer** **Role Name:** Machine Learning Engineer **Department Name:** AI & Data Science **Role GCF: 4a** **Hiring Manager Name:** Valentine Fontama _ABOUT AMGEN_ Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. _ABOUT THE ROLE_ _Role Description:_ We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join our team. 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. _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 DevOps/MLOps best practices to automate ML workflows and improve efficiency. * Develop and implement monitoring systems to track model performance and identify issues. * Conduct A/B testing and experimentation to optimize model performance. * Work closely with data scientists, engineers, and product teams to deliver ML solutions. * Stay updated with the latest trends and advancements _Must-Have Skills:_ * Solid foundation in machine learning algorithms and techniques * Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., D

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