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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Junior AI/ML Engineer - **Company:** CARPARTS INC. - **Location:** Long Beach, CA, United States - **Experience:** Starter - **Salary:** $105,000.0 - $115,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Automated Storage and Retrieval Systems, Automation of Tests, Big Data, Code Review, Continuous Integration, Data Cleansing, Elasticsearch, Github, Python (Programming Language), Machine Learning, Tensorflow, Search Technologies, SQL Databases, Transaction Data, Google Cloud, Chatbots, Pytorch, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Git, AI Platforms, Information Technology, HuggingFace, Data Analytics, Machine Learning Operations, Docker, Unsupervised Learning, Jenkins, Databricks - **Published:** September 13, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=24a3e16353933b0a ## About the Role * 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 ## Description 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 ## Related Videos - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? 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