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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 whats 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: 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, 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. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.