Job Description

Company Overview

Bain & Company is a global consultancy that helps the world's most ambitious change-makers define the future. Across 65 cities 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. We complement our tailored, integrated expertise with a vibrant ecosystem of digital innovators to deliver better, faster, and more enduring outcomes. Our 10-year commitment to invest more than $1 billion in pro bono services brings our talent, expertise, and insight to organizations tackling today's urgent challenges in education, racial equity, social justice, economic development, and the environment. 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.

WHAT YOU'LL DO

Design, build, and deliver statistical/ML models and agentic AI/LLM solutions to solve high-impact client problems. Architect and implement production-grade ML systems by building enterprise-grade services, applying MLOps and CI/CD for reliable deployment and monitoring, and ensuring high standards in engineering quality and documentation. Partner with software teams and client stakeholders to translate business problems into ML solutions, prioritize work, and enable enterprise?scale AI transformation. Continuously research emerging frameworks and state?of?the?art AI (e.g., LLMs, agents, retrieval, post-training, etc.) and convert learnings into reusable frameworks, components, and accelerators used across industries and functions. Share knowledge and mentor others on best practices tools, and approaches in applied machine learning and AI engineering. Contribute to internal R&D and learning initiatives to advance Bain's AI capabilities and foster continuous innovation between projects. Participate in hiring of other data science team members. Support individual team members and provide technical input and mentorship to help the team deliver current work in scope. Assess and help them improve their engineering practices. Advise business and technology partners on technology solutions leveraging emerging technologies and on mitigation of disruption risk.

Knowledge, Skills & Abilities

Programming & Data Processing

: Python, SQL, PySpark, Pandas, Apache Spark, Databricks, Delta Lake

Machine Learning Frameworks

: TensorFlow, scikit-learn, PyTorch, XGBoost, LightGBM

MLOps & Model Lifecycle

: MLflow, Kubeflow, Azure Machine Learning, Feature Stores, experiment tracking, automated retraining pipelines

Cloud & Infrastructure

: Azure ML, Azure Databricks, Synapse, ADLS, AKS, Azure Functions

Model Deployment & Scaling

: Dockerized models, REST/GRPC serving, AKS real-time inference, batch scoring, distributed/GPU training

DevOps & CI/CD

: Git, GitHub Actions, Azure DevOps, Terraform, automated ML pipeline deployments

Experience:

8-10 years of relevant experience; Advanced degree preferred. Strong theoretical and practical experience in machine learning Proficiency in Python, with solid software engineering foundations -- including clean code practices, testing, version control, and CI/CD workflows. Experience with cloud platforms (e.g., AWS, GCP, Azure) and deploying ML/AI applications. Comprehensive understanding of the ML lifecycle, from experimentation and model development to deployment. Experience productionizing and exposing ML models (e.g., using FastAPI, Flask, or similar frameworks) for seamless integration into applications and platforms. Excellent communicator and collaborator, able to align with technical and business stakeholders in a fast-paced, cross-functional environment. Curious and growth-oriented, passionate about exploring new tools, mentoring peers, and sharing best practices. Adaptable and self-driven, comfortable operating with autonomy, embracing feedback, and learning new skills to deliver client impact. Strong communication, time management and customer service skills * High performance and standards as demonstrated by academic and previous job experience.