New

Machine Learning Engineer

McKinsey & Company
parental leave, paid time off
United States, California, San Jose
Apr 02, 2025
Technology & Digital Machine Learning Engineer Job ID: 96744 Do you want to work on complex and pressing challenges-the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you've come to the right place. Your Impact 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 Growth 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 qualifications and skills 3 + years experience developing production oriented systems in Python is required. Experience with R preferred 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. Bachelor's degree preferred in computer science or related field Please review the additional requirements regarding essential job functions of McKinsey colleagues. Apply Now Apply Later FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity 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. Certain US jurisdictions require McKinsey & Company to include a reasonable estimate of the salary for this role. For new joiners for this role in the United States, including all office locations where the job may be performed, a reasonable estimated range is $108,200 - $141,800 USD -to help you understand what you can expect. This reflects our best estimate of the lowest to highest [salary/hourly wages] for this role at the time of this posting, ensuring you have a clear picture right from the start, though it's important to remember that actual salaries may vary. Factors like your office location, your unique blend of experience and skills, start date and our current organizational needs all play a part in determining the final figure. Certain roles are also eligible for bonuses, subject to McKinsey's discretion and based on factors such as individual and/or organizational performance. Additionally, we provide a comprehensive benefits package that reflects our commitment to the wellness of our colleagues and their families. This includes medical, mental health, dental and vision coverage, telemedicine services, life, accident and disability insurance, parental leave and family planning benefits, caregiving resources, a generous retirement contributions program, financial guidance, and paid time off. 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 Apr 01 00:00:00 GMT 2025 LinkedIn Posting City - Atlanta LinkedIn Posting State/Province - Georgia LinkedIn Posting Country - United States LinkedIn Job Title - Machine Learning Engineer LinkedIn Function - Information Technology LinkedIn Industry - Computer Software;Information Technology and Services LinkedIn Seniority Level - Mid-Senior level