Principal Machine Learning Engineer (Remote/Virtual) at US Foods #vacancy #remote

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The Principal ML Engineer plays a crucial role in bridging the gap between the development and deployment of machine learning models while ensuring an efficient transition of functional AI models from the lab to real-world production environments. The focus of Principal ML Engineer(s) is to build and automate ML CI/CD pipelines, containerize ML models, orchestrate infrastructure, and monitor and maintain the implementation by retraining and tracking metrics over time. This role independently owns at least one ML pipeline and has experience collaborating and engaging with various stakeholders. Principal ML Engineer is also expected to mentor junior ML Engineers and assist in their interactions with various other stakeholders including Data Scientists, SRE, domain experts, and other team members.

The Principal ML Engineer provides thought leadership for the ML team with broad application across the project portfolio. They are involved in planning ML initiatives and have foresight and broader picture/context to ensure alignment of downstream impact. The Principal ML Engineer is involved in data science projects from the inception and has an in-depth view of development and project goals. They are involved in setting up the final deliverables and coordinating with the entire ML team to ensure expectations are met. They are perceived as the experts in the field of MLOps and their expertise is sought-after by the data science and product teams. The Principal ML Engineer is responsible for establishing best practices and ensuring they are followed by the entire team.

This position is remote/virtual which means the work can be completed from anywhere in the United States except Hawaii or United States Territories.

We are unable to provide sponsorship for employment visa status (e.g., OPT, F-1, H-1B visa status). Candidates who require sponsorship and are not eligible to work in the United States are not eligible to apply.

This position is virtual/remote which means the work can be completed from anywhere in the United States except Hawaii or United States Territories.

We are unable to provide sponsorship for employment visa status (e.g., OPT, F-1, H-1B visa status). Candidates who require sponsorship and are not eligible to work in the United States are not eligible to apply.

RESPONSIBILITIES

As Principal ML Engineer, you will be expected to work in close coordination with Associate ML Engineers, ML Engineers, Sr. ML Engineers, Lead ML Engineers, and the Director of ML on:

Providing thought leadership to the ML Engineering team by sharing the foresight and broader picture/context with the team along with diverse and independent perspectives on technology and implementation

Leading the collaboration with cross-functional teams and examining wholistic ML engineering processes while emphasizing the scalability of the teams efforts

Collaborating with the Director of ML on defining the overall technical roadmap for all projects including customized and complex initiatives

Collaborating with the Director of ML in continuously reviewing, adding, and updating the roadmaps based on changes in requirements, technology, and resources

Assisting the director in budgeting resources and ensuring the most economical methods are used for achieving a given task

Overseeing the development and deployment of multiple pipelines and infrastructure to support ML models / products

Guiding the team in maintaining the production ML models by retraining the models on new data, fixing bugs, and adding new features

Advising the team in troubleshooting machine learning problems by identifying the root cause of problems and developing solutions to fix them

Collaborating with the Director of ML in establishing and following best practices for coding and deployment of MLOps pipelines by the entire team

Overseeing the provision of production support to the technical team to manage/troubleshoot the failure of an application

Overseeing the documentation of the production deployment with details regarding ML pipelines and associated technical infrastructure

Proactively leading and contributing to coding review sessions and developing mastery of coding conventions

Building an agile culture of prototyping and creating POC (proof of concepts) to demonstrate the feasibility of MLOps solutions

Guiding the team in supporting scalable ML solutions that efficiently handle increasing data volume, ensuring that the models remain effective and responsive as the business grows

Guiding the team in supporting the integration of machine learning models into processes that require efficient, automated responses

Promoting the usage of robust monitoring systems for deployed models, promptly identifying, and addressing issues to ensure continuous reliability and performance including data and model drift

Guiding the team in implementing machine learning features/solutions that enhance the overall user experience

Evangelizing and establishing the development standards, including coding standards and development methodologies

Other duties as assigned by manager

RELATIONSHIPS

Internal: ML Team (Associate ML Engineers, Sr. ML Engineers, ML Engineers, Lead ML Engineers, Director, ML), SRE, Product Management team, Data Science team, CX/UX team.

External: None.

WORK ENVIRONMENT

Remote: This role is fully remote, and the associate is expected to perform assigned responsibilities from a home-based environment.

MINIMUM QUALIFICATIONS

As a Principal ML Engineer, you have:

Masters degree or Bachelors degree plus 5-7 years of relevant professional Software Development experience.

Effective written, verbal, and interpersonal communication skills, with the ability to work and communicate effectively with team members

Demonstrated ability to effectively present to the stakeholders across functions and domains including senior leadership

Ability to share accountability and ownership in conversations with stakeholders

Ability to research the latest trends/ technologies/ architecture in ML space and contribute to research and innovation

Expert-level understanding of salient machine learning algorithms (for example: NLP, recommender systems) and model development lifecycle

5+ years experience with Agile/SCRUM methodologies

5+ years experience in AWS (or other clouds) relevant to machine learning including data processing & storage, API development, MLOps, CI/CD pipelines, and container orchestration (preferably ECS & EKS)

5+ years experience in using popular machine-learning frameworks

5+ years practical experience in scripting languages (preferably Python and Bash scripting)

5+ years experience in data warehouses & data lakes and analytics services, such as Snowflake

3+ years experience in distributed computing concepts preferably (for example, AWS Elastic MapReduce) for processing large datasets

5+ years experience in version control systems/concepts, such as Git

5+ years experience in SQL and NoSQL

5+ years experience in orchestration tools like Airflow or Dagster

3+ years experience working with structured, unstructured, and semi-structured data

5+ years experience in serverless technologies

5+ years experience in cloud computing, Linux OS, Docker, RDBMS, and NoSQL Databases

Deep expertise in the tech stack (Python, AWS Sagemaker, Snowflake, Dagster, dbt) with a focus on innovation and strategic application in ML.

Leadership in technical strategy and vision for ML applications.

Strong ability to mentor and develop technical talent.

Exceptional problem-solving and analytical skills to drive decision-making.

Up to 5% travel required, depending on business needs.

The following information is provided in accordance with certain state and local laws. Compensation depends on experience, geographic locations, and other factors permitted by law. In Colorado, the expected compensation for this role is between $141,800.00 and $189,000.00. In New York, the expected compensation for this role is between $132,600.00 to $210,400.00. In California and Washington, the expected compensation for this role is between $149,900.00 and $199,900.00. This role is also eligible for an annual incentive plan bonus. Benefits for this role include health insurance, pre-tax spending accounts, retirement benefits, paid time off, short-term and long-term disability, employee stock purchase plan, and life insurance. To review available benefits, please click here: .

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US Foods is one of Americas great food companies and a leading foodservice distributor, partnering with approximately 300,000 restaurants and foodservice operators to help their businesses succeed. With 28,000 employees and more than 70 locations, US Foods provides its customers with a broad and innovative food offering and a comprehensive suite of e-commerce, technology and business solutions. US Foods is headquartered in Rosemont, Ill., and generates more than $28 billion in annual revenue. Visit to learn more.

US Foods may collect personal information from you in connection with the application process. US Foods complies with the California Privacy Rights Act of 2020, and its policy may be found here ( .

US Foods, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other basis prohibited by applicable law.

EEO is the Law poster is available here ( .

EEO is the Law poster supplement is available here ( .

Pay Transparency policy statement is available here ( .

US Foods is committed to working with and providing reasonable accommodation to individuals with disabilities. If reasonable accommodation is needed to participate in the interview process or to perform essential job functions, please contact our US Foods Application Accommodation Line at . You will be prompted to leave a message. Please state the specifics of the assistance needed and your contact information. A member of our HR department will return your call within two business days.

Git Natural language processing (NLP) CI/CD API Python Artificial intelligence (AI) Amazon Web Services (AWS) Linux snowflake-cloud-data-platform amazon-ecs MLOps Docker amazon-eks SQL Airflow Machine Learning Bash RDBMS NoSQL dagster Amazon SageMaker DBT

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