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Technology & Digital

Machine Learning Engineer

Job ID: 92000
  • San Jose
  • Sao Paulo
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Are you driven by the opportunity to tackle complex challenges and work alongside top leaders? Do you want to be part of a team that delivers outcomes that others simply can’t? If so, you’ve come to the right place.

Who You'll Work With

At McKinsey, our most valuable resource is our people. As such, we have built a world class team dedicated to optimizing people management and facilitating data driven decision making, including strategies to improve employee satisfaction, team structure, employee management, recruiting decisions and other high impact use cases.
The People Analytics and Measurement team is globally respected as a leader in its field. You will be provided the opportunity for in-depth exposure to new, emerging methodologies through hands-on client projects, e-learning, certifications, live boot camps and global analytics conferences. This team works in one of the fastest growing disciplines in analytics.
You will be part of the technology architecture and enablement pod. You will contribute to a diverse, curious, entrepreneurial and innovative team that operates at the intersection of cloud computing, architecture, operations alongside natural language processing (NLP) and machine learning (ML). Each member of the team is motivated by personal and technical growth and enjoys a highly autonomous working environment along with team oriented projects.

Your impact within our firm

You will deal with Product and Services architecture and you will work at the intersection of other pods that deal with Data Engineering, Data Integration, Application Development and Data Science.  
You should be able to deploy ML, NLP and other similar solutions in a production environment at scale. You will be given ownership across the entire Software Engineering and Ops Lifecycle with a strong emphasis on Machine Learning Engineering to deploy models, and training, inference and validation pipelines into production. In the process, you will be supported and encouraged to become a Technology Architect. You will work with Data Engineers, Developers, Analysts and Product Owners to build scalable, reliable, and impactful services. You will be creating and maintaining stable, performant services (real-time, streaming, batch and scheduled) and applications that will deal with prescriptive analytics pre-dominantly which will help in driving firm decisions on the basis of large data-sets within the firm. 
You will design, implement, deploy into the cloud, and integrate state-of-the-art machine learning services at scale in production into critical firm workflows that need to be availed for stakeholders and users to serve the following use-cases - recruitment, trainings for firm members, team composition, staffing, satisfaction of your colleagues, etc.
You will build self-serve tools and services that will be leveraged by Product Owners and non-tech colleagues to analyze and to distill unstructured text data into actionable insights. For example, you will deploy solutions that analyze unstructured text like resumes, job descriptions, surveys, and other firm documents to help with use-cases in recruiting, staffing, etc.
You will architect scalable and performant solutions for the firm’s use-cases; provision and support Platforms, Tools, and Services necessary to drive Advanced Analytics, BI initiatives, and AI/ML opportunities in the People Technology space; conduct Discoveries and in-depth analysis of Cloud Services and SaaS platforms to determine the optimal tech stack for the team. You will develop NLP, ML Ops, and other capabilities for data scientists across the firm to use; aid Development teams with activities related to Architecture diagrams, Cloud Infrastructure setup and Security. 

Your qualifications and skills

  • Applied understanding of Natural Language processing techniques and Gen AI (e.g. language transformers / Large Language Models, text embeddings, and topic modeling), Statistical methods (e.g. linear and logistic regression), Machine Learning methods and optimization (e.g. boosted trees and deep neural networks), and graph algorithms with efficacy metrics
  • Prior experience with Infrastructure as Code (IaC) using solutions like Cloud Formation, Terraform or similar tools; developing CI/CD automation (primarily using GitHub actions, ArgoCD)
  • Hands on experience working with AWS services such as the ones related to Networking (VPC, Load Balancers), Compute (ECS, EKS, EC2), Storage (S3), Serverless (Lambda), API Gateway, Data Science services (Sagemaker), etc.
  • Experience developing production oriented systems in Python is required. Experience with R preferred
  • Bachelor’s degree preferred in computer science or related field

Please review the additional requirements regarding essential job functions of McKinsey colleagues.
Industries
  • High Tech
Capabilities
  • Technology
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FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.

FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.

FOR BRAZILIAN APPLICANTS: Applicants for job positions in any office in Brazil have flexibility regarding qualifications and McKinsey & Company will not require previous experience of more than 6 months. If the job description indicates preferred prior work experience of more than 6 months, applicants for such job position in the Brazilian offices must interpret the preferred qualification described as limited up to 6 months maximum.

Job Skill Group - CSSA
Job Skill Code - SSTE - Cloud Infrastructure Engineer II
Function - Technology
Industry - High Tech
Post to LinkedIn - Yes
Posted to LinkedIn Date - Tue Aug 15 00:00:00 GMT 2023
LinkedIn Posting City - San Jose
LinkedIn Posting State/Province -
LinkedIn Posting Country - Costa Rica
LinkedIn Job Title - Machine Learning Engineer
LinkedIn Function - Information Technology
LinkedIn Industry - Computer Software;Information Technology and Services
LinkedIn Seniority Level - Mid-Senior level