Gen AI Engineer - DTS

Metro Global Solution Center (MGSC) is internal solution partner for METRO, a €29.8 Billion international wholesaler with operations in 31 countries through 661 stores & a team of 93,000 people globally. Metro operates in a further 10 countries with its Food Service Distribution (FSD) business and it is thus active in a total of 34 countries.

MGSC, location wise is present in Pune (India), Düsseldorf (Germany) and Szczecin (Poland). We provide 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.

Website: https://www.metro-gsc.in
Company Size: 600-650
Headquarters: Pune, Maharashtra, India
Type: Privately Held
Inception:  2011

We are seeking a talented and passionate GenAI Engineer to join our dynamic team and contribute to the development and deployment of cutting-edge generative AI solutions. This role will focus on leveraging Google Cloud Platform (GCP) services to build scalable and robust AI applications. You will be instrumental in designing, implementing, and optimizing large language models (LLMs), diffusion models, and other generative AI techniques. 

Responsibilities: 

       Design and Development:  

• Develop and deploy generative AI models (LLMs, diffusion models, etc.) on GCP, utilizing services like Vertex AI, Cloud Storage, and BigQuery. 

• Design and implement scalable and efficient data pipelines for training and deploying generative AI models. 

• Build and maintain APIs and microservices for integrating generative AI capabilities into applications. 

• Develop and implement prompt engineering strategies to optimize LLM performance. 

• Analyze complex datasets, identify trends, and uncover insights that drive business strategies and optimizations.  

• Develop and implement statistical models, machine learning and deep learning algorithms to solve business problems and improve operational efficiency.  

• Collaborate with cross-functional teams to understand business requirements, formulate data-driven solutions, and present findings to stakeholders.  

• Apply data visualization techniques to effectively communicate complex analytical results and make recommendations for action.  

• Perform exploratory data analysis and data preprocessing tasks to ensure data quality and integrity 
  
  GCP Expertise:  

• Utilize Vertex AI for model training, deployment, and management. 

• Leverage Cloud Storage for data storage and retrieval. 

• Employ BigQuery for data analysis and feature engineering. 

• Implement serverless solutions using Cloud Functions or Cloud Run. 

• Manage and optimize GCP resources for cost-effectiveness and performance. 
  
  Model Optimization and Evaluation:  

• Fine-tune and optimize pre-trained models for specific use cases. 

• Evaluate model performance using appropriate metrics and techniques. 

• Conduct research and experimentation to explore new generative AI techniques. 
  
  Collaboration and Communication:  

• Collaborate with data scientists, software engineers, and product managers to deliver AI solutions. 

• Communicate technical concepts clearly and effectively to both technical and non-technical audiences. 

• Contribute to the development of best practices and documentation. 
  
  Stay Updated:  

• Keep abreast of the latest advancements in generative AI and GCP. 

• Participate in conferences, workshops, and online communities. 

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.    

• Strong understanding of generative AI concepts and techniques (LLMs, diffusion models, GANs, etc.). 

• Proficiency in Python and experience with deep learning frameworks (TensorFlow, PyTorch). 

• Extensive experience with Google Cloud Platform (GCP) services, particularly Vertex AI, Cloud Storage, and BigQuery. 

• Experience with data pipelines and data engineering. 

• Strong problem-solving and analytical skills. 

• Excellent communication and collaboration skills. 

• Experience with prompt engineering. 

• Experience with deploying AI models in production environments. 

• Experience with containerization (Docker, Kubernetes). 

• Experience with MLOps practices. 

• Experience with building chatbots, or other conversational AI products.