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Day 29
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Reads like a ML Engineer role: putting models into production.
Pune, Maharashtra, India
Live, first seen by us 29 days agoWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Design and optimize end-to-end ML pipelines for training, testing and deployment
Monitor deployed models for performance, accuracy and drift
Turn experimental models into production-grade solutions with data scientists
Create and maintain APIs that deliver ML results to internal teams and customers
Mentor and support junior engineers and data scientists
Design and optimize end-to-end machine learning pipelines for training, testing, and deployment in production environments
implement monitoring solutions to track performance, accuracy, and drift over time
Collaborate with data scientists to transition experimental models to production-grade solutions
Create and maintain APIs or other interfaces to deliver machine learning results to internal teams and Metro’s customers
Mentor and support junior engineers and data scientists, enabling their growth and success
8 years of hands-on experience in building and deploying machine learning models in production. Strong technical background and current modern BI and reporting technologies;
Proven experience in leading or mentoring technical teams;
Proficiency in Python, Go and machine learning frameworks;
Strong understanding of MLOps tools and practices, including CI/CD pipelines, model versioning, and monitoring;
Proficient with data transformation tools (preferable dbt);
Expertise in GCP services such a Cloud Run, Kubernetes, BigQuery and VertexAI;
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 29
Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Proven experience in leading or mentoring technical teams; - Proficiency in Python, Go and machine learning frameworks; - Strong understanding of MLOps tools and practices, including CI/CD pipelines, model versioning, and monitoring;
- Proficient with data transformation tools (preferable dbt); - Expertise in GCP services such a Cloud Run, Kubernetes, BigQuery and VertexAI; - Solid skills in API development and automated testing;
- Strong understanding of MLOps tools and practices, including CI/CD pipelines, model versioning, and monitoring; - Proficient with data transformation tools (preferable dbt); - Expertise in GCP services such a Cloud Run, Kubernetes, BigQuery and VertexAI;
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Your Responsibilities:
Required key competencies and qualifications:
Metro Global Solution Center (MGSC) is internal solution partner for METRO, a €31 Billion international wholesaler with operations in more than 30 countries. The store network comprises a total of 623 stores in 21 countries, of which 522 offer out-of-store delivery (OOS), and 94 dedicated depots. In 12 countries, METRO runs only the delivery business by its delivery companies (Food Service Distribution, FSD).
HoReCa and Traders are core customer groups of METRO. The HoReCa section includes hotels, restaurants, catering companies as well as bars, cafés and canteen operators. The Traders section includes small grocery stores and kiosks. The majority of all customer groups are small and medium-sized enterprises as well as sole traders. METRO helps them manage their business challenges more effectively.
MGSC, location wise is present in Pune (India), Düsseldorf (Germany) and Szczecin (Poland). We provide HR, Finance, IT & Business operations support to 31 countries, speak 24+ languages and process over 18,000 transactions a day. We are setting tomorrow’s standards for customer focus, digital solutions, and sustainable business models. For over 10 years, we have been providing services and solutions from our two locations in Pune and Szczecin. This has allowed us to gain extensive experience in how we can best serve our internal customers with high quality and passion. We believe that we can add value, drive efficiency, and satisfy our customers.
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Pune, Maharashtra, India
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