Junior AI/ML Engineer

We are looking for an AI/ML Engineer to join our team and play a key role in building, deploying, and advancing our machine learning and AI systems. This person will work cross-functionally to design, train, and ship models and agentic AI pipelines that power areas such as search, recommendations, content generation, customer segmentation, and conversational AI, owning the work end to end from SQL and data preparation through production deployment.YOU WILL:

• Design, train, evaluate, and deploy machine learning and deep learning models (e.g., ranking, retrieval, embeddings, NER, classification) that power search, recommendations, and other product experiences
• Build and maintain agentic AI pipelines that orchestrate LLMs, tools, and retrieval to automate data enrichment, content generation, and internal workflows
• Write efficient SQL and Python to build training datasets, features, and evaluation sets from large-scale clickstream, catalog, and transaction data
• Own the full model lifecycle: version code and models in GitHub, automate training and deployment through Jenkins CI/CD pipelines, and monitor model quality in production
• Collaborate with engineering, product, and marketing teams to integrate models and AI services into production systems
• Evaluate model performance with offline metrics and online A/B tests, and iterate based on results
• Stay current with advancements in AI/ML, including LLMs, agents, and representation learning, and identify opportunities to apply emerging techniques

• Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field with 2 years of professional experience in data science, machine learning, or a related role, or a Master’s degree in one of those fields
• Strong ML fundamentals: supervised and unsupervised learning, loss functions and optimization, regularization, evaluation metrics, and experiment design

• Hands-on deep learning experience training and fine-tuning models with PyTorch; familiarity with Hugging Face Transformers, TensorFlow, or similar frameworks

• Proficiency in Python and SQL, including writing and optimizing queries over large datasets
• Proficiency with Git and GitHub workflows (branching, pull requests, code review) and CI/CD tools such as Jenkins for automated testing, training, and deployment
• Experience building LLM-based or agentic AI pipelines (prompt design, tool use, RAG, evaluation)
• Experience working with large datasets and cloud platforms (e.g., Databricks, AWS, GCP)
• Good communication skills and ability to explain technical findings to non-technical stakeholders
• Bachelor’s or Master’s degree in Data Analytics, Statistics, Marketing, Business Analytics, or a related quantitative field, * Experience with e-commerce or retail product data
• Experience with search and retrieval systems (e.g., OpenSearch/Elasticsearch, vector search, learning-to-rank)
• Familiarity with MLOps tooling (e.g., MLflow, Docker, model serving and monitoring) and agent frameworks (e.g., LangGraph, MCP)
• Experience with end-to-end model development, from prototyping to production

CarParts.com is the go-to eCommerce platform for auto care and maintenance. We provide drivers with quality parts at competitive prices and enable them to schedule appointments with trusted mechanics directly through our website. Using world-class design principles and the latest technologies, we deliver a fast, intuitive digital experience backed by our company-owned national distribution network.

With over 1,000 employees worldwide, we are scaling rapidly, fueled by our most recent strategic partnership and $35 million investment. This positions us for the next phase of growth as we continue to empower drivers along their journey.

Our Culture At CarParts.com, our culture goes beyond our core values of Safety First, Customer Focused, and Commitment to Excellence. We are a performance-driven, data-focused, and fast-paced team where results matter and winning is expected.

• Hungry & Hardworking: We set ambitious goals, measure progress with clear metrics, and hold ourselves accountable to deliver results.
• Promote from Within: We reward top performers with opportunities for growth and advancement.

• Collaborative & In-Person: We believe the best ideas and fastest execution happen face-to-face.

• High Standards: We move quickly, pay attention to details, and dig deep - whether it’s analyzing contracts, aggregating complex scenarios, or building clear, data-driven presentations.
• No Passengers: We value grit, ownership, and the relentless pursuit of results