Lead Machine Learning Engineer (MLops)

General Mills; Mumbai; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

General Mills India, part of the Global Data Science team, seeks a Lead ML Engineer to drive end-to-end MLOps pipelines on Google Cloud Platform using Vertex AI, Kubeflow, and Airflow. You will automate deployment, monitoring, and retraining while establishing best practices and guiding cross-functional teams.

You will mentor engineers, optimize cloud costs, and push for scalable, production-ready ML solutions across the organization.

Qualifications

• Bachelor's degree in CS, engineering, or data science.
• 7+ years in MLOps; 12+ years in industry.
• Strong Python, SQL/BigQuery, and Vertex AI on GCP.
• Hands-on with Airflow, Kubeflow, MLflow, and CI/CD.

Responsibilities

• Design, develop, and implement end-to-end MLOps pipelines on GCP (Vertex AI).
• Automate model deployment, monitoring, retraining, logging, and orchestration.
• Mentor team members and promote knowledge sharing across Data Science and Engineering teams.
• Drive ML architecture standards and platform improvements across the organization.

Skills

Python programming

SQL/BigQuery

MLOps concepts

Agile development

Mentorship

Education

Bachelor's degree in CS/Engineering/Data Science

Tools

Vertex AI

Airflow

Kubeflow

MLflow

Git

Jenkins

Job description

COMPANY OVERVIEWWe exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best — bold thinkers with big hearts who challenge one another and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what’s next.OVERVIEWGeneral Mills, Digital and Technology India, is seeking a Lead ML Engineer to join our dynamic and innovative Global Data Science team. In this role, you are a critical member of the data science group focused on leading efforts in migrating ML-based solutions from concept to production-level operational excellence. You will lead initiatives building scalable, resilient, and automated solutions in GCP (Google Cloud Platform) to ensure that models deliver on organizational objectives.KEY ACCOUNTABILITIESDesign, develop, and implement end-to-end MLOps pipelines using GCP, Vertex AI, Kubeflow, and Airflow .Automate model deployment, monitoring, retraining, logging, and ML pipeline orchestration .Establish and drive MLOps best practices , including version control, CI/CD, coding standards, and quality assurance.Optimize ML model performance, deployment processes, cloud infrastructure, and operational efficiency .Lead production support , troubleshoot issues, perform root cause analysis, and implement preventive solutions.Partner with Data Science, Engineering, and Business teams to deploy scalable, production-ready ML solutions.Drive ML architecture standards, reusable design patterns, and platform improvements across the organization.Research and adopt emerging MLOps technologies and best practices to enhance scalability and reduce cloud costs.Mentor team members, promote knowledge sharing, and foster a collaborative engineering culture.Continuously enhance technical expertise through learning and adoption of new technologies.MINIMUM QUALIFICATIONSEducation: Minimum Bachelor's degree, Advanced degree in a quantitative field (CS, engineering, statistics, math, data science).Experience: Relevant Machine Learning experience of 7+ years in MLOps and overall 12+ years of Industry experienceTechnical Skills:Strong proficiency in Python , SQL/BigQuery, and Vertex AI on GCP .Experience building and deploying production-scale ML models with performance optimization.Hands-on experience with Airflow, Kubeflow, MLflow , and MLOps orchestration.Knowledge of CI/CD, TDD, Jenkins , and version control tools such as Git .Experience working in Agile (Scrum/Kanban) development environments.Strong understanding of supervised ML algorithms , data transformation, and feature engineering.Passion for learning new technologies and solving complex engineering problems.Soft Skills: Strong verbal and written communication skills including the ability to interact effectively with colleagues of varying technical and non-technical abilities.PREFERRED QUALIFICATIONSGCP Machine Learning certification , Understanding of CPG industryExposure to Deep Learning/RL/LLMsPublications or contributions to the data science and AI community.Certifications in AI, machine learning, or related fields.ELIGIBILITYApplicants must meet minimum age qualifications in the country in which the job is located.