MLOps Engineer with experience in Healthcare and Life Sciences

In the rapidly evolving domain of AI/ML, the MLOps role is a linchpin in ensuring the seamless transition of machine learning models from development to production. With a blend of expertise in both machine learning and operational best practices, MLOps engineer is the driving force behind the deployment, monitoring, and management of AI systems.

Xenon7 is a Consulting company focused on helping companies understand Data, AI, and ML space and implement solutions and strategies based on these technologies in the best possible way while also applying AI ethics and Infosec Regulations and Principles.  We bring in rich experience in various industries and technology capabilities including Healthcare and Life Sciences, Financial Services, Retail, CPG, Media, and others.

We are seeking MLOps engineers who have experience in the Healthcare and Life Sciences domain and can navigate the complexity and specificity of it, ensuring that the deployment of machine learning technology in healthcare settings is safe, effective, and compliant with all necessary standards and regulations.

Responsibilities:

As MLOps your responsibilities include but are not limited to:

• Deploying and operationalizing MLOps, in particular, implementing:
• Model hyperparameter optimization
• Model evaluation and explainability
• Model training and automated retraining
• Model workflows from onboarding, operations to decommissioning
• Model version tracking & governance
• Data archival & version management
• Model and drift monitoring
• Creating and using benchmarks, metrics, and monitoring to measure and improve services.
• Providing best practices and executing POC for automated and efficient model operations at scale.
• Designing and developing scalable MLOps frameworks to support models based on client requirements.
• Being the MLOps expert for the sales team, providing technical design solutions to support RFPs.

• Establish and maintain relationships with third parties/vendors
• Create and maintain comprehensive project documentation

Requirements

• US citizen or Greencard holder
• 5+ years of experience in Software Engineering, DevOps, or Data Science/ML roles
• 2+ years of experience as MLOps
• 2+ years of experience in Healthcare and Life Sciences domain
• Familiarity with cloud platforms like AWS, Azure, or GCP, including knowledge of services like EC2, S3, SageMaker, or Google Cloud ML Engine for scalable and efficient model deployment.
• Experience with Docker and container orchestration platforms like Kubernetes.
• Experience with Quality Assurance using experiment tracking and workflow versioning.
• Proficiency in data ingestion, pipelines, transformation, and storage technologies (e.g., SQL, NoSQL, Hadoop, Spark).
• Experience with machine learning frameworks such as PyTorch, TensorFlow, and TFX.
• Knowledge of version control (e.g., Git), CI/CD tools (e.g., Jenkins), and infrastructure automation (e.g., Ansible, Terraform)
• Experience with unit/integration testing and monitoring tools (e.g., Prometheus, ELK Stack) and logging frameworks (e.g., Logstash, Fluentd)
• A strong sense of teamwork and communication skills to collaborate with data scientists, engineers, and stakeholders
• High fluency in English (equivalent to C2 or professional level)

Benefits

• Work From Home
• Training & Development
• Meet and collaborate with other extremely smart people
• Meet and work with CIOs, CTOs, and other important people from big companies
• Work on exciting cutting-edge projects