LEAD ENGINEER - Machine Learning

Happiest Minds Technologies; Pune District; On-site; INR 1,500,000 - 2,700,000; Full time

Job summary

Happiest Minds Technologies is seeking an experienced MLOps engineer in Pune to design and maintain scalable ML pipelines. You will collaborate with data scientists to deploy models, optimize performance in production, and ensure governance and security across deployments.

The role requires hands-on experience with MLflow, Kubeflow or TFX, Python/R, and cloud ML services, along with Docker and Kubernetes for containerization. Opportunity to work in a fast-paced, Agile environment.

Qualifications

• Strong knowledge of machine learning concepts and algorithms.
• Experience with MLOps tools and frameworks (MLflow, Kubeflow, TFX).
• Proficiency in programming languages such as Python and R.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Experience with containerization technologies (Docker, Kubernetes).
• Strong understanding of CI/CD processes and tools (Jenkins, GitLab CI).
• Knowledge of data preprocessing, feature engineering, and model evaluation techniques.

Responsibilities

• Design, implement, and maintain MLOps pipelines for deploying machine learning models.
• Collaborate with data scientists to understand model requirements and translate them into production-ready solutions.
• Monitor and optimize the performance of machine learning models in production.
• Develop and maintain documentation for MLOps processes and workflows.
• Implement CI/CD practices for machine learning projects.
• Ensure compliance with data governance and security policies.
• Provide technical support and troubleshooting for deployed models.
• Stay updated with the latest trends and technologies in MLOps and machine learning.

Skills

ML concepts

MLOps tools

Python

R

Cloud platforms

Docker

Kubernetes

CI/CD

Jenkins

GitLab CI

Data preprocessing

Feature engineering

Model evaluation

Big data

Tools

MLflow

Kubeflow

TFX

Job description

Responsibilities:

• Design, implement, and maintain MLOps pipelines for deploying machine learning models.
• Collaborate with data scientists to understand model requirements and translate them into production-ready solutions.
• Monitor and optimize the performance of machine learning models in production.
• Develop and maintain documentation for MLOps processes and workflows.
• Implement CI/CD practices for machine learning projects.
• Ensure compliance with data governance and security policies.
• Provide technical support and troubleshooting for deployed models.
• Stay updated with the latest trends and technologies in MLOps and machine learning.

Mandatory Skills:

• Strong knowledge of machine learning concepts and algorithms.
• Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, TFX).
• Proficiency in programming languages such as Python and R.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their ML services.
• Experience with containerization technologies (e.g., Docker, Kubernetes).
• Strong understanding of CI/CD processes and tools (e.g., Jenkins, GitLab CI).
• Knowledge of data preprocessing, feature engineering, and model evaluation techniques.

Preferred Skills:

• Experience with big data technologies (e.g., Hadoop, Spark).
• Familiarity with data visualization tools (e.g., Tableau, Power BI).
• Knowledge of DevOps practices and tools.
• Experience in working with cross-functional teams in an Agile environment.