Lead, Machine Learning Engineer

Employment type

Permanent Full-Time

Description & Requirements


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 a Glassdoor Best Place to Work, and we have maintained a spot in the top four since its founding in 2009. We believe that diversity, inclusion and collaboration are 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.


Working alongside our generalist consultants, Bain's Advanced Analytics Group (AAG) helps clients across industries solve their biggest problems using our expertise in data science, customer insights, statistics, machine learning, data management, supply chain analytics and data engineering. Stationed in our global offices, AAG team members hold advanced degrees in computer science, engineering, AI, data science, physics, statistics, mathematics, and other quantitative disciplines, with backgrounds in a variety of fields including tech, data science, marketing analytics and academia.


We are looking for someone who has:

  • 3-5 years of engineering experience 
  • Expert knowledge of Python and SQL 
  • Proficiency in one or more of R, Java, C++, Scala, Go, Julia. Familiarity with JavaScript Frameworks e.g. React, Vue is a plus. 
  • Track record of implementing statistical, machine learning and NLP models, deploying these and maintaining them in production environments 
  • Strong understanding of fundamental computer science concepts, particularly data structures, algorithms, automated testing, object-oriented programming, performance complexity, and implications of computer architecture on software performance 
  • Solid understanding of foundational concepts and algorithms in statistics and machine learning, including linear/logistic regression, SVM, random forest, boosting, neural networks, dimensionality reduction, reinforcement learning, etc. 
  • Experience with machine learning frameworks and tools (e.g. Pandas, numpy, scikit-learn, TensorFlow, Pytorch, Keras, Huggingface) 
  • Understanding of probabilistic programming techniques and associated tools (e.g. Pyro, Stan, Tensorflow Probability, PyMC3), Bayesian inference and MCMC methods 
  • Experience using, designing and developing microservices and associated APIs, with a thorough understanding of REST, GraphQL, gRPC 
  • Understanding of data security and privacy regulations, key topics in cybersecurity, authentication and authorization mechanisms (including cloud IAM) 
  • Experience with MLOps (scalable development to deployment of complex data science workflows) and associated tools, e.g. MLflow, Kubeflow 
  • Experience with containers, Docker and Git 
  • Experience working in accordance with DevSecOps principles, and familiarity with industry deployment best practices using CI/CD tools and infrastructure as code (Jenkins, Docker, Kubernetes, and Terraform) 
  • Experience with cloud platforms (e.g. AWS, GCP, Azure, Databricks, etc) and associated machine learning products, e.g. Amazon SageMaker, Azure ML 
  • Experience in big data technologies, e.g. Hadoop, BigQuery, MapReduce, Apache Spark  
  • Experience working according to agile principles 
  • Strong interpersonal and communication skills, including the ability to explain and discuss technicalities of ML algorithms and techniques with colleagues and clients from other disciplines 
  • Ability to work independently and juggle priorities to thrive in a fast paced and ambiguous environment, while also collaborating as part of a team in complex situations 



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. We earned a platinum rating from EcoVadis, the leading platform for environmental, social, and ethical performance ratings for global supply chains, putting us in the top 1% of all companies. 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.