Machine Learning Engineer II (MLOps)
通用磨坊股份有限公司 · Pune, Maharashtra, India
Manufacturing · 10,001+ employees
About the role
The Machine Learning Engineer will build and maintain scalable MLOps pipelines using GCP, Vertex AI, and Airflow to support enterprise data and model needs. They are responsible for the end-to-end lifecycle of ML models, including deployment, monitoring, retraining, and performance optimization.
What they look for
Requirements
Candidates must have a bachelor's degree and at least 6 years of analytical experience, with a minimum of 3 years specifically in AI and Machine Learning. Proficiency in Python, SQL, GCP services, and MLOps best practices is required for this role.
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 Machine Learning Engineer II to join the Enterprise Data Capabilities Organization. This team builds enterprise-level scalable and sustainable data and model pipelines to serve the analytic needs of business and high-impact problem statements. In this role, you are a critical member of the data science team focused on operationalizing the ML and AI models, which entail model management and monitoring too. The success is to recommend innovative ways to automate the MLOps pipelines on GCP and set standards that would ensure repeated success.
KEY ACCOUNTABILITIES
- Implement and support end-to-end MLOps pipelines using GCP, Vertex AI, Airflow/Kubeflow, and related tools.
- Build and maintain feature engineering, deployment, monitoring, retraining, and CI/CD/CT pipelines for production ML solutions.
- Ensure ML model lifecycle management, including monitoring, performance optimization, and operational support.
- Follow and recommend MLOps best practices, coding standards, version control, and technical documentation.
- Collaborate with Data Science, Data Engineering, Cloud Platform, and MLOps teams to deliver scalable ML solutions.
- Communicate project progress, risks, and outcomes effectively while contributing to knowledge sharing across teams.
- Continuously enhance technical expertise by adopting emerging MLOps technologies, tools, and best practices.
MINIMUM QUALIFICATIONS
- Education: Bachelor’s degree (full time)
- Experience: Total 6+ years of analytical experience with atleast 3+ years of experience in AI and Machine Learning
- Technical Skills: Expertise in Data Transformation and Manipulation through Big-Query/SQL, professional experience with Vertex AI and GCP Services, Strong expertise in Python for designing and running ML pipelines along with Airflow/Cloud composer/Kubeflow Experience, Building and maintaining project specific custom containers.
- Soft Skills: Strong communication skills both verbal and written including the ability to interact effectively with colleagues of varying technical and non-technical Passionate about agile software processes, data-driven development, reliability, and systematic experimentation
PREFERRED QUALIFICATIONS
- Google Cloud Platform Machine Learning (GCPML) certification
- Understanding of the Consumer-Packaged Goods (CPG) industry
- Strong understanding of Core Machine Learning Algorithms

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