Summary of Role/Position
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
YOU MUST HAVE:
- 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
NICE TO HAVE:
- 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
A reasonable salary estimate based on education, experience, and geographic location is: $105,000-$115,000
The above-noted job description is not intended to describe, in detail, the multitude of tasks that may be assigned but rather to give the incumbent a general sense of the responsibilities and expectations of his/her position. As the nature of business demands change so, too, may the essential functions of this position.
