MLOps Engineer

Greetings from BMW Techworks India

Role: MLOPS Engineer

Location: Bangalore or Chennai

Experience: 6 to 12 Years

What awaits you/ Job Profile:

• Design and Implementation: Develop and implement a robust MLOps framework and infrastructure to support the deployment and maintenance of machine learning models.
• Machine Learning Model Deployment: Oversee the deployment of machine learning models into production environments, ensuring they are scalable and reliable.
• Monitoring and Maintenance: Continuously monitor the performance of deployed models, making necessary adjustments to maintain optimal performance and stability.
• Automation: Implement CI/CD pipelines for automation of model deployment, monitoring, and updates to ensure pipeline stability.
• Collaboration: Work closely with data scientists and stakeholders to translate business requirements into technical specifications and ensure alignment on project goals.
• Documentation: Maintain comprehensive documentation of MLOps processes, model performance, and system architecture to facilitate knowledge sharing and compliance.

What should you bring along:

• Educational Background: A degree in Computer Science, Data Science, Mathematics, or a related field.
• Experience: Proven experience in MLOps, data analysis, and software development, with a strong emphasis on designing and maintaining MLOps frameworks.
• Problem-Solving Mindset: Strong analytical skills and the ability to approach complex problems with innovative solutions.
• Team Player: Excellent communication skills and the ability to work effectively in a team-oriented environment.

Must have technical skill:

• MLOps Framework Expertise: In-depth knowledge of robust MLOps practices, including the design and provision of MLOps frameworks and infrastructure.
• AWS AI/ML Services: Proficiency in using AWS AI/ML service stacks, such as AWS SageMaker and AWS Nova, for model deployment and maintenance.
• Programming Languages: Proficiency in PySpark for Data Engineering and ETL
• Machine Learning Frameworks: Familiarity with frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• AWS Data Engineering: Strong skills in AWS ETL services, data engineering, and Cloud data ingestion.
• CI/CD Automation: Experience in implementing CI/CD for automation, monitoring, and ensuring pipeline stability.
• Communication Skills: Ability to translate business needs into technical implementations and vice versa, ensuring alignment between stakeholders and technical teams.
• Initiative and ownership: Ability to independently identify and address issues, take responsibility for actions and outcomes, and proactively initiate ideas, share, and contribute to the team's success

Good to have skills:

• Understanding of statistical methods and algorithms used in machine learning.
• Design Skills: A strong inclination towards exploring AI/ML solution design, acting not only as a developer but also as a solution designer.
• Big Data Technologies: Experience with big data technologies such as Hadoop, Spark, or Kafka.
• Version Control and IaaC: E.g., GitHub and Terraform.