Lead Machine Learning Engineer (MLops)

Posted Yesterday
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Powai, Mumbai Suburban, Maharashtra, IND
In-Office
Expert/Leader
Food
The Role
Leads the design and implementation of scalable MLOps pipelines on GCP using Vertex AI, Kubeflow, Airflow, and MLflow. Automates model deployment, monitoring, retraining, logging, and orchestration while establishing CI/CD, quality, and architecture standards. Provides production support, troubleshooting, optimization, and root cause analysis; partners with data science, engineering, and business teams; researches emerging technologies; and mentors engineers.
Summary Generated by Built In

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.

Skills Required

  • Minimum bachelor's degree in computer science, engineering, statistics, mathematics, data science, or a related quantitative field
  • 7+ years of relevant machine learning experience in MLOps
  • 12+ years of overall industry experience
  • Proficiency in Python, SQL or BigQuery, and Vertex AI on GCP
  • Experience building and deploying production-scale machine learning models with performance optimization
  • Hands-on experience with Airflow, Kubeflow, MLflow, and MLOps orchestration
  • Knowledge of CI/CD, test-driven development, Jenkins, and Git
  • Experience working in Agile development environments, including Scrum or Kanban
  • Understanding of supervised machine learning algorithms, data transformation, and feature engineering
  • Strong verbal and written communication skills
  • GCP Machine Learning certification
  • Understanding of the consumer packaged goods industry
  • Exposure to deep learning, reinforcement learning, or large language models
  • Publications or contributions to the data science and AI community
  • Certifications in AI, machine learning, or related fields
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The Company
HQ: Minneapolis, MN
21,000 Employees
Year Founded: 1928

What We Do

We exist to make food the world loves. But we do more than that. General Mills 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 other and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what’s next.

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