Junior AI/ML Engineer

• Design, train, evaluate, and deploy machine learning and deep learning models for search, recommendations, and other product experiences
• Build and maintain agentic AI pipelines that orchestrate LLMs, tools, and retrieval for 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, including versioning code and models in GitHub, automating training and deployment through Jenkins CI/CD pipelines, and monitoring production model quality
• Collaborate with engineering, product, and marketing teams to integrate models and AI services into production systems
• Evaluate model performance using offline metrics and online A/B tests, iterating based on results
• Stay current with AI/ML advancements, including LLMs, agents, and representation learning, and identify opportunities to apply emerging techniques

Requirements 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 Experience building LLM-based or agentic AI pipelines (prompt design, tool use, RAG, evaluation) Experience working with large datasets and cloud platforms such as Databricks, AWS, or 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 such as OpenSearch/Elasticsearch, vector search, or learning-to-rank Familiarity with MLOps tooling such as MLflow and Docker, model serving and monitoring, and agent frameworks such as LangGraph or MCP Experience with end-to-end model development, from prototyping to production Core Competencies Demonstrates expertise in designing, training, and deploying machine learning and deep learning models, with a strong focus on building agentic AI pipelines and optimizing model performance. Proficient in Python, SQL, and MLOps practices, ensuring effective collaboration across engineering, product, and marketing teams. Highest-signal resume keywords Machine Learning Fundamentals Deep Learning with PyTorch Python and SQL Proficiency CI/CD with Jenkins Experience with LLM-based AI Pipelines ATS Optimization Keywords Hard Skills Machine Learning Deep Learning SQL Python Model Evaluation Data Science Model Deployment Data Enrichment Feature Engineering Experiment Design Soft Skills Good Communication Skills Industry Keywords E-commerce Retail Product Data Search and Retrieval Systems OpenSearch Elasticsearch Vector Search Learning-to-Rank Agent Frameworks LangGraph MCP Tools & Technologies Git GitHub Jenkins Hugging Face Transformers TensorFlow Databricks AWS GCP MLflow Docker #J-18808-Ljbffr Jobtailor