ML Ops Engineer

Greetings from TCS!!!

TCS presents an excellent opportunity for Techno Functional Role!

Role: ML Ops Engineer

Desired Experience Range: 5-10 Years

Location: PAN

Desired Competencies (Technical/Behavioral Competency)

Must-Have

• Several years of practical experience in applying machine learning and data science methods in a business context

• Profound knowledge of relevant programming languages and frameworks (e.g., Python, R, scikit-learn, PyTorch)

• Experience working with databases (e.g., SQL) and ideally big data technologies (e.g., GCP Big Query).

• Ideally, expertise in neural networks, especially autoencoders and transformers, to elevate our solutions to the next level.

• Experience with cloud platforms and CI/CD processes (e.g. Github Actions) for data products is advantageous.

• Extensive knowledge of the banking industry, mainly in client transactions, transaction monitoring using anomaly detection algorithms.

• Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP)

• Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift

• Programming languages like Python, Go, Ruby or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.

• Ability to understand tools used by data scientist and experience with software development and test automation

• Fluent in English, good communication skills and ability to work in a team

Key responsibilities:

• Design and implement cloud solutions, build MLOps on cloud (AWS, Azure, or GCP)

• Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, Airflow or similar tools

• Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality

• Data science models testing, validation and tests automation

• Communicate with a team of data scientists, data engineers and architect, document the processes