Machine Learning Engineer

2 hours ago

Bengaluru, IndiaMid Level / Senior

Responsibilities

Build and maintain machine learning CI/CD pipelines for automated testing, model deployment, and version control.
Deploy machine learning models as scalable APIs and microservices that meet clinical performance and latency requirements.
Implement monitoring for model performance, data drift, and production system health.
Develop and optimize ETL pipelines for FHIR and HL7 healthcare data used in model training and inference.
Build and maintain feature stores and data layers that provide consistency between training and production environments.
Integrate machine learning outputs into core healthcare applications with backend engineering teams.
Write clean, maintainable, and documented Python code and participate in code reviews.
Use Docker and Kubernetes to package and orchestrate machine learning workloads.
Ensure data handling and deployments follow HIPAA and HITRUST security standards.

Bachelor’s or master’s degree in computer science, software engineering, data engineering, or a related field.
Three to five years of professional software engineering or data engineering experience, including at least two years focused on machine learning production environments.
Strong Python proficiency and familiarity with SQL.
Hands-on experience with at least one major cloud provider and Docker.
Familiarity with PyTorch or Scikit-learn and MLOps tools such as Airflow, Prefect, BentoML, or Kubeflow.
Experience with data processing frameworks such as Pandas, Spark, or dbt.
Knowledge of a compiled language such as Go or Java is a plus.
Familiarity with deploying large language models or using LangChain is a plus.
Experience in a regulated environment and understanding of API design and microservices architecture are additional qualifications.

Hybrid work arrangement in Bangalore.
Travel may include up to 10% domestic travel.
Solventum offers programs supporting physical and financial well-being and regularly benchmarks pay and benefits for competitiveness.