Full-Time Sr. ML Ops Eng

Datavant is a data platform company for healthcare whose products and solutions enable organizations to move and connect data securely. Datavant has a network of networks consisting of thousands of organizations, more than 70,000 hospitals and clinics, 70% of the 100 largest health systems, and an ecosystem of 500+ real-world data partners. By joining Datavant today, you're stepping onto a highly collaborative, remote-friendly team passionate about creating transformative change in healthcare.

We invest in our people and believe in hiring for high-potential and humble individuals who can rapidly grow their responsibilities as the company scales. Datavant is a distributed, remote-first team, and we empower Datavanters to shape their working environment to suit their needs.

About the role: We seek a skilled MLOps Engineer with expertise in Spark, Python, GPU, and preferably Databricks. As an MLOps Engineer, you will play a critical role in operationalizing and automating machine learning workflows, ensuring scalability, reliability, and efficiency.

You will collaborate closely with data scientists, software engineers, and DevOps teams to deploy, monitor, and manage machine learning models in production environments.

Daily responsibilities include:

• Design, implement, and maintain scalable MLOps infrastructure and pipelines using Apache Spark, Python, and other relevant technologies.
• Collaborate with data scientists and software engineers to deploy machine learning models into production environments.
• Develop and automate CI/CD pipelines for model training, testing, validation, and deployment.
• Implement monitoring, logging, and alerting solutions to track model performance, data drift, and system health.
• Optimize and tune machine learning workflows for performance, scalability, and cost efficiency.
• Ensure security and compliance requirements are met throughout the MLOps lifecycle.
• Work closely with DevOps teams to integrate machine learning systems with existing infrastructure and deployment processes.
• Provide technical guidance and support to cross-functional teams on best practices for MLOps and model deployment.
• Stay updated on emerging technologies, tools, and best practices in MLOps and machine learning engineering domains.
• Perform troubleshooting and resolution of issues related to machine learning pipelines, infrastructure, and deployments.

What you bring to the table:

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• Proven experience (5+ years) as a MLOps Engineer, Software engineer, DevOps Engineer or related role.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.
• Strong understanding of machine learning concepts, algorithms, and frameworks such as MLFlow, TensorFlow, PyTorch, or Scikit-learn.
• Knowledge of big data processing technologies such as Apache Spark.
• Experience with cloud platforms and familiarity with relevant services.
• Understanding of containerization technologies and container orchestration tools.
• Proficiency in version control systems and CI/CD tools.
• Hands-on experience with Databricks (nice to have).
• Experience designing and implementing CI/CD pipelines for machine learning workflows using tools like Jenkins, GitLab CI, or Azure DevOps.
• Strong problem-solving skills and attention to detail.

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