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:Bachelors 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, Solid 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: Solid 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
Robust understanding of Core Machine Learning Algorithms

ELIGIBILITY

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

📌 Ml Ops Engineer Mumbai
🏢 General Mills
📍 Mumbai