Senior Machine Learning Engineer

What you will do

Let’s do this. Let’s change the world. In this vital role 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 crucial 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 standard methodologies 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

 

What we expect of you 
We are all different, yet we all use our outstanding contributions to serve patients.





Basic Qualifications:

Doctorate degree

Or

Master’s degree and 4 to 6 years of Data Science or Machine Learning experience OR

Bachelor’s degree and 6 to 8 years of Data Science or Machine Learning experience OR

Diploma and 10 to 12 years of Data Science or Machine Learning experience

Preferred Qualifications:



 

Functional Skills: 


Must-Have Skills:

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., TensorFlow, PyTorch, Scikit-learn)

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

 

Good-to-Have Skills: 

Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing

Experience with data engineering and pipeline development

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

Familiar with AWS, Azure, or Google Cloud;

Familiar with Databricks platform for data analytics and MLOps

 

Professional Certifications 

Cloud Computing certificate preferred

Machine Learning and Data Science related certification preferred

 

Soft Skills: 

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 lead multiple priorities successfully.

Team-oriented, with a focus on achieving team goals

Strong presentation and public speaking skills

 

What you can expect of us 
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way.

In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.



 

Apply now 


for a career that defies imagination

Objects in your future are closer than they appear. Join us.



 

careers.amgen.com