Job Title: MLOps Engineer

Position Summary:

The MLOps Engineer position at MedRisk will be responsible for designing, implementing, and maintaining the infrastructure that will allow MedRisk to efficiently develop and deploy machine learning models. As an MLOps Engineer, you will work closely with data scientists, analysts, and IT professionals to build a robust and scalable machine learning platform. This position will take a lead role in the architecture of this platform, as well as its implementation and maintenance.

Candidates for this role must have excellent problem-solving skills, a solid technical background, and the ability to work collaboratively across different teams.

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Primary Duties & Responsibilities:

- Design and implement machine learning infrastructure, allow for the integration of ML services into various business-critical applications.
- Collaborate with data scientists to understand their needs for infrastructure and tooling.
- Develop and maintain CI/CD pipelines for machine learning workflows.
- Implement MLOps practices such as automated testing, version control, and deployment of ML models.
- Collaborate with IT and software development teams to ensure the infrastructure aligns with company-wide architectural standards.




- Monitor the performance of machine learning models in production and troubleshoot any issues that arise.
- Stay up-to-date with the latest industry trends and technologies in MLOps and machine learning.

Required Qualifications:

- Degree in Computer Science, Software Engineering, Data Science or other related field. Masters degree strongly preferred.
- Minimum of 3 years of experience in a similar role and 5 years of total experience.
- Strong experience with Azure cloud platform, particularly its machine learning and data processing services.
- Proficiency in Python and familiarity with machine learning libraries and frameworks such as TensorFlow, PyTorch, and Scikit-learn
- Experience with MLOps tools such as MLflow, Kubeflow, or Metaflow
- Knowledge of containerization technologies like Docker and Kubernetes
- Experience with orchestration tools such as Airflow, Prefect or Dagster
- Familiarity with CI/CD tools. Experience specifically with Azure DevOps services is a plus.
- Understanding of data management, including experience with databases (SQL and NoSQL), data warehousing solutions, and ETL processes.

Employment Type:

Full Time

📌 MLOps Engineer (Hyderabad)
🏢 Medrisk
📍 Hyderabad