Lead Machine Learning Engineer, MLOps

Lead Machine Learning Engineer (MLops)

Location: Powai, Mumbai, MH

Remote Type: Hybrid

Time Type: Full time

Job Description

COMPANY OVERVIEW

We 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.​

OVERVIEW

General 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 ACCOUNTABILITIES

  • Design, 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 QUALIFICATIONS

Education: 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 experience

Technical 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 QUALIFICATIONS

  • GCP Machine Learning certification, Understanding of CPG industry

  • Exposure to Deep Learning/RL/LLMs

  • Publications or contributions to the data science and AI community.

  • Certifications in AI, machine learning, or related fields.

ELIGIBILITY

Applicants must meet minimum age qualifications in the country in which the job is located.

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