Associate- AI/ML Engineer(Sustainability)
Indexed description
We are 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 13 years. We believe that diversity, inclusion, and collaboration is key to building extraordinary teams.
In 2004, Bain & Company opened the Bain Capability Network office in Gurgaon, to provide the best-in-class internal support, efficiently and professionally, to both leadership and consulting teams in Bain offices across the region and globe.
Who You Will Work With
- The AI/ML Associate in BCN Sustainability CoE plays a critical role in delivering high-impact AI and ML-driven solutions across internal tools and strategic initiatives. The role involves leading discrete ML workstreams and proof-of-concept (POC) initiatives, supporting complex digital builds under the guidance of senior team members, and delivering rigorous, data-driven outputs.
- The Associate may be staffed across diverse digital initiatives including ML model development, GenAI integration, workflow automation, experimentation frameworks, and AI-enabled product features. The Associate applies strong technical and analytical skills to translate structured problem statements into scalable AI solutions.
- The role requires a strong technical foundation, comfort working with structured and unstructured data, and the ability to operationalize ML/GenAI models in practical applications.
- AI / ML Development & Analysis
- Lead discrete ML or GenAI workstreams, ensuring high-quality technical delivery
- Translate business or product requirements into ML-driven analytical solutions
- Perform data preprocessing, feature engineering, and model experimentation
- Develop, train, evaluate, and refine ML models for POCs and internal applications
- Identify risks, technical trade-offs, and performance limitations early and propose alternative approaches
- Apply best prompt engineering techniques as per the use case(e.g., structured prompting, few-shot prompting, system prompts, response constraints)
- Integrate GenAI APIs (e.g., OpenAI, Azure OpenAI, or similar LLM services) into applications and workflows
- Combine LLM outputs with structured logic, APIs, and backend services
- Evaluate model outputs for reliability, bias, and usability, iterating to improve performance
- Build and maintain scalable ML pipelines and experimentation frameworks
- Support API-based deployment and integration of AI models into digital tools
- Leverage coding and automation tools (e.g., Python) to streamline workflows
- Explore emerging AI capabilities to improve efficiency and innovation across projects
- Collaborate closely with engineers, designers, and business stakeholders in a fast-paced environment
- Support larger digital initiatives under senior guidance while independently managing defined workstreams
- Communicate technical findings clearly to non-technical stakeholders
- Bachelor’s degree with approximately 2-4 years of relevant experience, or Master’s degree with 1-2 years of experience
- Educational background in Computer Science, Engineering, Data Science, Statistics, or related quantitative field
- Strong applied academic or project-based ML/AI
- Prior experience of working with consulting firms will be preferred (but not mandatory)
- Strong proficiency in Python
- Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn, or similar)
- Solid understanding of model evaluation, experimentation, and data preprocessing
- Working knowledge of GenAI tools and LLM integration
- Strong problem-solving skills and ability to synthesize technical findings into practical insights
- Ability to understand business and sector language/ specifics and integrate that into day-to-day working
- Excellent communication and collaboration skills, with the ability to operate effectively in dynamic, team-based consulting environments
- Sharp business acumen – ability to make sound decisions, recognize market/ sector knowledge of sustainability, operational understanding of consulting companies
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