Junior AI/ML Engineer

Jobtailor; California (MO); On-site; USD 120,000 - 190,000; Full time

Job summary

Jobtailor is seeking a data science professional to design, train, and deploy ML models for search and recommendations, and to build agentic AI pipelines that orchestrate LLMs, tools, and retrieval across enrichment, content generation, and internal workflows.

You will own the full model lifecycle, collaborate with engineering, product, and marketing, and evaluate performance with offline metrics and online tests, while staying current with AI advances.

Qualifications

• Bachelor's or Master's in a quantitative field with ML/data experience
• Strong ML fundamentals and experiment design
• Hands-on PyTorch DL training experience
• Familiarity with Hugging Face Transformers or TensorFlow
• Proficiency in Python and SQL for large datasets
• Git/GitHub and Jenkins CI/CD workflows
• Experience building LLM-based AI pipelines
• Experience with Databricks/AWS/GCP
• Good communication skills for non-technical stakeholders
• Experience with e-commerce or retail product data and search/retrieval

Responsibilities

• Design, train, evaluate, and deploy ML/DL models for search, recommendations, and product experiences
• Build and maintain agentic AI pipelines orchestrating LLMs, tools, and retrieval
• Write Python and SQL to build training data, features, and evaluation sets
• Own the full model lifecycle: versioning in GitHub, automated training and deployment via Jenkins, monitoring
• Collaborate with engineering, product, and marketing to integrate models into production
• Evaluate model performance with offline metrics and online A/B tests
• Stay current with AI/ML advancements and apply emerging techniques

Skills

Machine Learning Fundamentals

Deep Learning with PyTorch

Python and SQL Proficiency

CI/CD with Jenkins

LLM-based AI Pipelines

Education

Bachelor's degree in Computer Science, Statistics, Mathematics, or related field

Master's degree in CS/Statistics/Math or related field

Tools

Git

GitHub

Jenkins

Hugging Face Transformers

TensorFlow

Databricks

AWS

GCP

MLflow

Docker

Job description

• 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