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Expert Manager, Machine Learning Engineer
Location:
MX-Mexico City
Jobcode:
2502294
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WHAT MAKES US A GREAT PLACE TO WORK



We are proud to beconsistently recognizedas 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.



WHO YOULL WORK WITH



As a member of Bains Advanced Analytics Group, youll 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 YOULL 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




ABOUT US

Bain & Company is a global consultancy that helps the worlds most ambitious change makers define the future.

Across 64 cities in 39 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 todays 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.



Bain & Company

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