Associate – ML Engineer (Data Business CoE)

About us Bain & Company is a global management consulting that helps the world’s most ambitious change makers define the future. Across 65 offices in 40 countries, we work alongside our clients as one team with a shared ambition to achieve extraordinary results, outperform the competition and redefine industries. Since our founding in 1973, we have measured our success by the success of our clients, and we proudly maintain the highest level of client advocacy in the industry. In 2004, the firm established its presence in the Indian market by opening the Bain Capability Center (BCC) in New Delhi. The BCC is now known as BCN (Bain Capability Network) with its nodes across various geographies. BCN is an integral and largest unit of (ECD) Expert Client Delivery. ECD plays a critical role as it adds value to Bain's case teams globally by supporting them with analytics and research solutioning across all industries, specific domains for corporate cases, client development, private equity diligence or Bain intellectual property. The BCN comprises of Consulting Services, Knowledge Services and Shared Services.

Who you will work with We are looking for an ML Engineering Associate to support the Pyxis ML platform - the engine powering product taxonomy tagging, merchant classification, and data enrichment across Bain's consumer analytics capabilities. This is a great role for someone early in their career who is excited about the intersection of machine learning, cloud infrastructure, and real-world data products. Our ML Engineers partner directly with Data Operations so that their impact is directly tied to business and client outcomes.

What you’ll do ML Pipeline Support

• Support deployment and day-to-day operations of Pyxis ML microservices; including classifiers, clustering, LLM pipelines, and rule engines
• Manage training data curation across large datasets and own model development and deployment end to end
• Run and validate training and prediction pipelines for supervised and unsupervised models
• Monitor async job queues and help troubleshoot failures across Redis Queue (RQ), EC2 machines, and other routers
• Assist with model artifact management powering MLOps visibility and RCA
• Assist with Snowflake-based data ingestion, SQL rule resolution, and data management for model development
• Support LLM pipeline operations, including OpenAI/Anthropic batch jobs, token monitoring, and output validation LLM & GenAI Support
• Help manage OpenAI/Anthropic batch and synchronous completions pipelines
• Monitor token usage, job statuses, and flag anomalies
• Support prompt template updates and output validation Infrastructure & Deployment
• Support CI/CD workflows for ML services using GitHub Actions – Docker and Terraform builds, ECS deployments
• Help maintain containerized ML services on AWS
• Assist with S3 integrations, IAM configurations, and queue management Collaboration
• Work closely with Data Scientists and DevOps on pipeline onboarding
• Maintain documentation and runbooks for operational processes
• Partner directly with Client Success and Operations on model outputs for clients

About you About you

• 3-5 years of experience in a data, ML, or software engineering role
• Working knowledge of Python - exposure to FastAPI or similar frameworks is a plus
• Basic understanding of AWS services - S3, ECS, IAM
• Familiarity with Docker and containerization concepts
• Exposure to ML frameworks - TensorFlow/Keras or Scikit-learn
• Intermediate SQL skills and comfort working with cloud data warehouses like Snowflake

Good to have

• Exposure to CI/CD pipelines and GitHub Actions
• Familiarity with LLM APIs or prompt engineering
• Understanding of NLP/text vectorization concepts
• Interest in retail data, product taxonomy, or consumer analytics

What makes us a great place to work We are proud to be consistently recognized as one of the world's best places to work, a champion of diversity and a model of social responsibility. We are currently ranked the #1 consulting firm on Glassdoor’s Best Places to Work list, and we have maintained a spot in the top four on Glassdoor's list for the last 12 years. We believe that diversity, inclusion and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. We are publicly recognized by external parties such as Fortune, Vault, Mogul, Working Mother, Glassdoor and the Human Rights Campaign for being a great place to work for diversity and inclusion, women, LGBTQ and parents.