Expert Manager, Machine Learning Engineer

Key Skills

Apache Hadoop, AWS, Azure, Docker, Effective communication skills, Google BigQuery, Google Cloud Platform (GCP), Kubernetes-K8s, Machine learning techniques, NumPy, Scikit-learn

Job Description

WHO YOU’LL WORK WITH

As a member of Bain’s Advanced Analytics Group, you’ll join a talented team of diverse and inclusive analytics professionals who are dedicated to solving complex challenges for our clients. We work closely with our generalist consultants and clients to develop data-driven strategies and innovative solutions. Our collaborative and supportive work environment fosters creativity and continuous learning, enabling us to consistently deliver exceptional results.

WHAT YOU’LL DO

• 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

ABOUT YOU

• 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