Machine Learning Engineer
Description For Machine Learning Engineer
MSD (Merck Sharp & Dohme) is seeking a Machine Learning Engineer to join their Data Science and Scientific Informatics Team within Research and Development Sciences IT. This role presents an exciting opportunity to work at the intersection of healthcare and artificial intelligence, focusing on the deployment and operationalization of machine learning models across multiple domains.
The position involves working with cutting-edge MLOps technologies and practices, where you'll be responsible for designing and implementing features to support new MLOps use cases for a diverse range of models and platforms. You'll collaborate with data scientists, software engineers, and product teams to build robust and scalable analytics capabilities that drive innovation in healthcare.
The ideal candidate will bring strong technical expertise in Python, machine learning frameworks, and MLOps tools, combined with the ability to work effectively in a global, collaborative environment. You'll have the opportunity to work on meaningful projects that impact healthcare while enjoying the benefits of a flexible work environment and comprehensive benefits package.
Working at MSD means joining a global healthcare leader with a century-long legacy of innovation. The company offers excellent career growth opportunities, a supportive work culture, and the chance to contribute to groundbreaking healthcare solutions. The position offers a hybrid working model, competitive compensation, and extensive benefits including health insurance, pension contributions, and generous time off policies.
This role is perfect for someone who is passionate about machine learning, enjoys solving complex problems, and wants to make a meaningful impact in the healthcare industry while working with a diverse, global team of professionals.
Responsibilities For Machine Learning Engineer
- Collaborate with data scientists and teams to design and maintain production-level ML pipelines
- Develop and automate processes for data preprocessing and model training
- Implement MLOps principles for streamlined model deployment
- Monitor and evaluate model performance in production
- Present findings to internal stakeholders
- Stay current with industry trends in ML and MLOps
Requirements For Machine Learning Engineer
- Knowledge of machine learning algorithms and data science techniques
- Proficiency in Python with ML libraries (scikit-learn, TensorFlow, PyTorch)
- Experience with MLOps tools (MLFlow, Docker, SageMaker)
- Familiarity with Git, GitHub actions and CI/CD processes
- Experience with Apache Airflow
- Knowledge of big data technologies and cloud computing (AWS, Databricks, EC2)
- University degree in Computer Science, Data Science, Applied Mathematics, or related fields
- Strong analytical and problem-solving capabilities
- Excellent communication skills
Benefits For Machine Learning Engineer
- Hybrid working model with flexible role pattern
- Pension and health insurance contributions
- 5 weeks annual leave
- 5 sick days
- 15 days of certified sick leave
- 40 paid hours annually for volunteering
- 12 weeks of parental contribution
- Cafeteria benefits system
- Multisport Card
- Company laptop and iPhone
- Parking in the garage
- Competitive salary and incentive pay
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