MLOps Architect

MLOps Architect

Contract/Fulltime

Responsibilities:

• -The Senior MLOps Architect will be responsible for architecting and implementing scalable MLOps solutions
• .This role involves working closely with data scientists, data engineers, and software developers to ensure that machine learning models are efficiently deployed, monitored, and maintained
• .The ideal candidate will have a strong background in both machine learning and software engineering, with experience in deploying ML models in production environments
• .Architecture & Design: Design and implement scalable MLOps architectures and frameworks that support model development, deployment, monitoring, and lifecycle management
• .Pipeline Development: Develop, maintain, and optimize ML pipelines for data preprocessing, model training, validation, and deployment
• .Automation: Implement automation for CI/CD pipelines, testing, and monitoring of ML models in production. Infrastructure Management: Design and manage cloud-based and on-premises infrastructure for ML model training and deployment, including Kubernetes, Docker, and other relevant technologies
• .Collaboration: Work closely with data scientists, data engineers, software engineers, and DevOps teams to integrate ML models into existing systems and workflows
• .Monitoring & Performance: Implement monitoring and logging solutions to track model performance, data drift, and other critical metrics
• .Security & Compliance: Ensure that ML models and pipelines adhere to security best practices and regulatory requirements
• .Documentation & Best Practices: Create and maintain comprehensive documentation of MLOps processes, tools, and best practices
• .Mentorship & Leadership: Provide technical leadership and mentorship to junior team members and help build a culture of continuous learning and improvement

Experience:

• -10+ Yea

rs
Location

-· Rem

ote
Educational Qualification

• s: -Engineering Degree – BE/ME/BTech/MTech/BSc/
• MSc.Technical certification in multiple technologies is desira

ble.
Mandatory s

• killsTechnical Skills: Strong programming skills in Python, Java, or another programming lang
• uage.Experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-Le
• arn).Proficiency in cloud platforms (e.g., AWS, Azure, Google Cloud) and related services (e.g., S3, EC2, Lambda, Glue, SageMaker e
• tc.).Experience with containerization and orchestration technologies (e.g., Docker, Kuberne
• tes).Knowledge of CI/CD tools (e.g., Jenkins, GitLab CI/CD, Circl
• eCI).Familiarity with infrastructure-as-code tools (e.g., Terraform, CloudFormat
• ion).Strong understanding of data engineering principles and ETL processes. Soft Skills: Excellent problem-solving and analytical skills. Strong communication and interpersonal sk
• ills.Ability to work in a fast-paced, collaborative environ
• ment.Strong organizational and time management sk
• ills.Preferred Qualifications: Experience with model versioning and monitoring tools (e.g., MLflow, Kubeflow). Knowledge of data privacy and security regulat
• ions.Previous experience in the healthcare industry or payer domain (Prefer

red).