Senior MLOps Engineer

IMMEDIATE JOINERS ONLY

Job Title: Senior MLOps Engineer

Location

Note: DevOps -Knowledge is fine

Experience Range: 6-12 years

Primary Key skills: MLOps

Key Responsibilities:

• Design, develop and maintain end-to-end MLOps pipelines for model deployment, monitoring, maintenance, and scalability.
• Automate the retraining, testing, and validation processes for ML models.
• Collaborate with cross-functional teams, including data science, software engineering and DevOps, to integrate ML models into production systems.
• Monitor model performance, diagnose issues, and implement improvements.
• Ensure scalability, reliability, and compliance of ML systems in production.
• Optimize infrastructure costs while maintaining high system performance.
• Stay up-to-date with the latest developments in MLOps, machine learning and AI, and apply new techniques to improve existing models and processes.

Qualifications:

• Education:

  Bachelors or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.

Experience:

• Solid experience as a MLOps Engineer, Machine Learning Engineer, DevOps Engineer, or similar role.
• Experience in the retail industry or e-commerce is highly desirable.

Technical Skills:

• Strong experience with Infrastructure as Code frameworks and languages (Terraform, Bicep or ARM)
• Strong programming skills in Python and experience with ML frameworks (TensorFlow, PyTorch, etc.).
• Hands-on experience with containerization (Docker) and orchestration tools (Kubernetes).
• Proficiency in CI/CD tools and cloud platforms (AWS, Azure, or Google Cloud).
• Knowledge of model monitoring and evaluation metrics.
• Familiarity with version control systems, such as Git, and model versioning tools like MLflow or DVC.
• Experience with Generative AI product deployment is desirable.
• Experience with big data using Databricks, Snowflake, Apache Spark or Hadoop is desirable. – some of these
• System level architecture understanding including scaling, MLOps, model/data monitoring, andensuring a deterministic pipeline.

Soft Skills:

• Strong problem-solving skills with the ability to work independently and collaboratively in a fast-paced environment.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• A proactive attitude and a passion for continuous learning and innovation.