Expert Manager, Machine Learning Engineer
5 days ago
About Bain & Company Inc.
We are a leading management consulting firm that helps organizations make data-driven decisions to drive growth and success. Our team of experts is dedicated to solving complex business challenges using advanced analytics and machine learning techniques.
Job Summary
We are seeking a highly skilled Expert Manager, Machine Learning Engineer to join our Advanced Analytics Group. As a member of our team, you will work closely with our generalist consultants and clients to develop data-driven strategies and innovative solutions.
Key Responsibilities
- Work with general consulting teams to understand ML aspects of business problems, and appropriately prioritize and execute
- Provide technical leadership for end-to-end technical solution delivery on client cases (from solution architecture to hands-on development work)
- Advise client executives on topics in ML engineering and roadmap design
- Develop statistical/ML models to be handed over to clients as prototype or production software
- Transform existing prototype code into scalable, production-grade software
- Write, test, deploy and maintain machine learning code across the full software development lifecycle
- Codify client work into repeatable software toolkits and solutions
- Regularly demonstrate code to other team members
- Peer-review code contributions by other team members
- Collaborate on (or lead) the development of re-usable common frameworks, model and components that can be highly leveraged to address common ML engineering problems across industries and business functions
- Drive best demonstrated practices in software engineering, and share learnings with team members in AAG about theoretical and technical developments in ML engineering
- Work with the team and other senior leaders to create a great working environment that attracts other great ML engineers
- Act as PD Advisor as needed
- Participate in recruiting and onboarding for other team members
Requirements
- 7+ years of engineering experience
- 1+ years of experience managing data scientists / machine learning engineers
- Shipped production, enterprise scale data products
- Expert knowledge of Python and SQL
- Proficiency in one or more of R, Java, C++, Scala, Go, Julia
- Strong track record of implementing statistical and machine learning 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.
- Broad experience of 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 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, Containers, Git)
- 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
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