MLOps + DevOps Engineer

2 weeks ago


Delhi Gurugram NCR Noida, India Innova AM Tech Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Notice:- Immediate Joiners Only

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 Masters 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, and ensuring 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.



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