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通用磨坊股份有限公司

Lead Machine Learning Engineer (MLops)

通用磨坊股份有限公司 · Mumbai, Maharashtra, India

Manufacturing · 10,001+ employees

3 d ago
Principal (10+ yrs) Full-time India
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About the role

You will lead the migration of machine learning solutions from concept to production by designing and implementing scalable MLOps pipelines. Additionally, you will drive architecture standards, automate model deployment and monitoring, and mentor team members to foster a collaborative engineering culture.

What they look for

Python SQL BigQuery Vertex AI GCP Airflow Kubeflow MLflow CI/CD Jenkins Git MLOps Feature Engineering Supervised Learning Agile TDD

Requirements

The role requires a minimum of 7 years of relevant MLOps experience and 12 years of total industry experience, along with a Bachelor's or advanced degree in a quantitative field. Candidates must possess strong proficiency in Python, SQL, and GCP-based machine learning tools, as well as experience in Agile development environments.

Full 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.