Job description

Work Your Magic with us! Start your next chapter and join EMD Serono. Ready to explore, break barriers, and discover more? We know you’ve got big plans – so do we! Our colleagues across the globe love innovating with science and technology to enrich people’s lives with our solutions in Healthcare, Life Science, and Electronics. Together, we dream big and are passionate about caring for our rich mix of people, customers, patients, and planet. That's why we are always looking for curious minds that see themselves imagining the unimaginable with us. United As One for Patients, our purpose in Healthcare is to help create, improve and prolong lives. We develop medicines, intelligent devices and innovative technologies in therapeutic areas such as Oncology, Neurology and Fertility. Our teams work together across 6 continents with passion and relentless curiosity in order to help patients at every stage of life. Joining our Healthcare team is becoming part of a diverse, inclusive and flexible working culture, presenting great opportunities for personal development and career advancement across the globe. Your Role At EMD Serono, data, analytics, and AI are core to how we bring innovative medicines to patients faster. As a Senior Data & MLOps Engineer, you own the data and MLOps foundations - from ingestion to production - collaborating with Data Science, Commercial, Medical, Analytics, and IT to turn prototypes into scalable, governed solutions. Key Responsibilities • Build, maintain, and troubleshoot scalable data pipelines, ETL/ELT workflows, derived tables, curated datasets, and feature-ready data assets using SQL and Python. • Deploy and operationalize machine learning, advanced analytics, and generative AI solutions through automated deployment, monitoring, and operational workflows. • Enable GenAI use cases involving embeddings, vector databases, retrieval-augmented generation, prompt management, and evaluation workflows. • Establish reusable engineering patterns, CI/CD practices, testing frameworks, documentation, and governance standards for data and ML solutions. • Apply data privacy, security, quality, lineage, access control, and compliance standards appropriate for healthcare and pharmaceutical data. This will be a hybrid role - in office 3 days per week/2 days per week work from home. Who You Are Minimum Qualifications • Bachelor’s degree in computer science, Engineering, or a related technical field, or equivalent work experience. • 4+ years of experience in data engineering, MLOps, machine learning engineering, software engineering, cloud engineering, or related technical roles. • Hands-on experience building production data pipelines, ETL/ELT workflows, derived tables, curated datasets, or feature-ready data assets. • Experience deploying or operationalizing machine learning models, advanced analytics workflows, or AI-enabled solutions. • Advanced SQL, Python, and shell scripting. • Proven track record of architecting, deploying, and maintaining complex projects in a diverse ecosystem of AWS services. Experience with AWS automation through CloudFormation and Azure DevOps. • Experience with Git, CI/CD, containerization, and production software engineering practices, including troubleshooting build failures. • Familiarity with model monitoring, model versioning, experiment tracking, testing, and deployment automation. Experience with designing proactive alerting and monitoring workflows for workloads running on AWS services. • Strong communicator who works independently and collaborates effectively across technical and business stakeholders Preferred Qualifications • 7+ years of experience across data engineering, MLOps, ML engineering, analytics engineering, or software engineering. • Experience in pharmaceutical, biotechnology, healthcare, or life sciences environments and datasets such as claims, EMR/EHR, patient services, customer engagement, field activity, marketing, or sales data. • Experience with Snowflake, dbt, Airflow, IICS or equivalent ETL/orchestration tools, parquet files, and large-scale data processing patterns. • Experience with AWS ML/data services, MLflow, SageMaker, Kubeflow, Docker, Kubernetes, or Terraform. • Experience implementing data quality checks, data observability, lineage, pipeline monitoring, model monitoring, drift detection, batch inference, real-time inference, or automated retraining. • Hands-on experience with GenAI applications (RAG, vector databases, LLM evaluation) • Nice to have • AWS certifications - AWS Certified DevOps Engineer Professional; AWS Certified Data Engineer • Experience with Tableau, Power BI, or other BI tools for data visualization and reporting. Pay Range for this position: $137,800 - 206,600 The offer range represents the anticipated low and high end of the base pay compensation for this position. The actual compensation offered will be determined by factors such as location, level of experience, education, skills, and other job-related factors. Position may be eligible for sales or performance-based bonuses. Benefits offered by the Company include health insurance, paid time off (PTO), retirement contributions, and other prequisites. For more information click here . What we offer: We are curious minds that come from a broad range of backgrounds, perspectives, and life experiences. We believe that this variety drives excellence and innovation, strengthening our ability to lead in science and technology. We are committed to creating access and opportunities for all to develop and grow at your own pace. Join us in building a culture of inclusion and belonging that impacts millions and empowers everyone to work their magic and champion human progress! Apply now and become a part of a team that is dedicated to Sparking Discovery and Elevating Humanity!

Requirements

Must-haves

Work Your Magic with us! Start your next chapter and join EMD Serono.
Build, maintain, and troubleshoot scalable data pipelines, ETL/ELT workflows, derived tables, curated datasets, and feature-ready data assets using SQL and Python.
Deploy and operationalize machine learning, advanced analytics, and generative AI solutions through automated deployment, monitoring, and operational workflows.
Enable GenAI use cases involving embeddings, vector databases, retrieval-augmented generation, prompt management, and evaluation workflows.
Establish reusable engineering patterns, CI/CD practices, testing frameworks, documentation, and governance standards for data and ML solutions.
Apply data privacy, security, quality, lineage, access control, and compliance standards appropriate for healthcare and pharmaceutical data.
This will be a hybrid role - in office 3 days per week/2 days per week work from home.
Bachelor’s degree in computer science, Engineering, or a related technical field, or equivalent work experience.
4+ years of experience in data engineering, MLOps, machine learning engineering, software engineering, cloud engineering, or related technical roles.
Hands-on experience building production data pipelines, ETL/ELT workflows, derived tables, curated datasets, or feature-ready data assets.
Experience deploying or operationalizing machine learning models, advanced analytics workflows, or AI-enabled solutions.
Advanced SQL, Python, and shell scripting.
Proven track record of architecting, deploying, and maintaining complex projects in a diverse ecosystem of AWS services. Experience with AWS automation through CloudFormation and Azure DevOps.
Experience with Git, CI/CD, containerization, and production software engineering practices, including troubleshooting build failures.
Familiarity with model monitoring, model versioning, experiment tracking, testing, and deployment automation. Experience with designing proactive alerting and monitoring workflows for workloads running on AWS services.
Strong communicator who works independently and collaborates effectively across technical and business stakeholders

Nice-to-haves

Experience in pharmaceutical, biotechnology, healthcare, or life sciences environments and datasets such as claims, EMR/EHR, patient services, customer engagement, field activity, marketing, or sales data.
Experience with Snowflake, dbt, Airflow, IICS or equivalent ETL/orchestration tools, parquet files, and large-scale data processing patterns.
Experience with AWS ML/data services, MLflow, SageMaker, Kubeflow, Docker, Kubernetes, or Terraform.
Experience implementing data quality checks, data observability, lineage, pipeline monitoring, model monitoring, drift detection, batch inference, real-time inference, or automated retraining.
Hands-on experience with GenAI applications (RAG, vector databases, LLM evaluation)
AWS certifications - AWS Certified DevOps Engineer Professional; AWS Certified Data Engineer
Experience with Tableau, Power BI, or other BI tools for data visualization and reporting.
Apply now and become a part of a team that is dedicated to Sparking Discovery and Elevating Humanity!

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aisqlpythonmachine learningci/cdmlawsazuredockerkubernetesllm

Platform: phenom
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Pto

Paid Time Off