Impact

As a Staff Machine Learning Engineer on Shipt's Personalization Platform team you will drive key AI initiatives. In this role, you’ll collaborate with Data Scientists to design and deploy intelligent, personalized recommendation models to drive user engagement across Shipt. You will be a hands-on senior technical contributor in the Membership organization and your work will consist of contribution to architecture, design, and implementation to deliver high quality AI driven solutions in a rapidly evolving marketplace environment.
In this role you will design, build and maintain scalable ML infrastructure and production systems as well as closely collaborate with Data Scientists to architect data pipelines for serving and training ML models for Shipt's Personalization Platform. You will also be responsible for leading the team to build scalable, low-latency, and fault-tolerant systems to serve real-time recommendations at scale and developing robust APIs and services to deliver real-time or batch recommendations (using Python, Go). This is a hands-on, cross-functional role ideal for someone who thrives at the intersection of Machine Learning, AI Engineering, and Business Impact.

• 5+ years of experience in machine learning and backend software engineering

• Proficiency in at least one backend programming language (e.g., Go, Java) and Python

• Deep understanding of user modeling, embeddings, similarity search and ranking models

• Strong experience with serving architectures (e.g., REST/gRPC APIs, model servers)

• Experience with ML pipeline tools (e.g., MLflow, Kubeflow, Airflow)

• Strong grasp of distributed systems, microservices, and system design

• Experience with SQL and NoSQL databases and working with large-scale datasets

• Exposure to experimentation platforms and online A/B testing.

Skills & Education

This list includes key skills used in this job but is not inclusive of all skills needed for the role. Please see any required education below.

Back-End Development, Machine Learning (ML), Python (Programming Language), Structured Programming

 

Bachelor's Degree or equivalent experience | Required

 

 

Work Arrangement

Shipt considers candidates located near a Shipt office or workspace in Birmingham, San Francisco, or Minneapolis to be hybrid, which means that they have the flexibility to work from home (with leader approval) or at a Shipt office in order to facilitate the ability to innovate, collaborate, and spark team connections. In-office expectations will vary by role and leader.  Certain roles may require in-office presence on a full-time basis. Please work with your recruiter to learn more about the classification of this role.

About Shipt

Shipt is a retail tech company that connects people to reliable, high-quality delivery with a personal touch. Shipt connects customers to the things they want from the stores they love, retail businesses to more satisfied customers, and workers to new earning opportunities.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or any other characteristic protected by law.

Please inform your recruiting contact upon initial connection if you need a reasonable accommodation. If you need assistance filling out a job application, please complete this form. 

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Employees (and eligible family members) are covered by medical, dental, vision and more.  Employees may enroll in our company’s 401k plan. Employees will also be eligible to receive discretionary vacation for exempt team members, paid holidays throughout the calendar year and paid sick leave.  Other compensation includes eligibility for an annual bonus and the potential for restricted stock units based on role.