AI/ML Engineer

SFE; Woodlands (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

SFE is seeking an hands-on AI/ML Engineer in Woodlands, CA to design, build, and deploy production-grade ML and GenAI solutions. You will leverage Python expertise to implement end-to-end pipelines, including prompt engineering for LLMs, document processing, and embedding-based search.

The role focuses on end-to-end ML workflows, integrating vector databases and MongoDB, and ensuring scalable, production-ready deployments with CI/CD and cloud platforms.

Qualifications

• Strong Python expertise with production-grade ML experience.
• Hands-on experience deploying GenAI/LLM use cases.
• Experience building document processing pipelines and vector search.
• Familiarity with vector databases and MongoDB integration.
• Ability to design scalable ML solutions from data to production.

Responsibilities

• Design, build, and deploy production-grade ML/GenAI solutions.
• Develop and optimize prompt engineering for LLM-based systems.
• Build Retrieval-Augmented Generation pipelines with vector search.
• Integrate LLMs via APIs into enterprise applications.
• Develop agentic AI workflows and tool calling capabilities.
• Implement CI/CD and cloud deployment with observability.
• Collaborate with data engineers, product owners, and platform teams.
• Stay updated on evolving ML/GenAI tech and apply to projects.

Skills

Python

ML training

GenAI & LLMs

Prompt engineering

Document processing

Embeddings

Vector search

Vector databases

MongoDB

Production ML engineering

Job description

Must Have Technical/Functional Skills

• Python (Expert level)
• Machine Learning & Model Training
  • Training, evaluation, fine tuning
  • Tagging and labeling workflows
• Generative AI & LLMs
  • Prompt engineering for LLM-based applications
• Document Processing
  • Document extraction, parsing, and chunking
  • Handling structured & unstructured data
• Embeddings & Vector Search
  • Embedding generation
  • Vector database integration
• Databases
  • Vector Databases
  • MongoDB
• Production-grade ML Engineering
  • Scalable, production-ready ML/GenAI solutions

Roles & Responsibilities

This role is for a hands-on AI/ML Engineer who will design, build, and deploy production grade Machine Learning and Generative AI solutions. The candidate must have strong Python expertise and practical experience taking ML and GenAI use cases from development to deployment.

The role focuses heavily on LLM-based applications, including prompt engineering, document processing pipelines, and embedding-based search solutions. The engineer will work with both structured and unstructured data, building pipelines for document extraction, parsing, and chunking, and integrating ML models with Vector Databases and MongoDB.

An ideal candidate is someone who understands end-to-end ML workflows-from data preparation, tagging, and labeling, through model training, evaluation, and fine-tuning-while ensuring solutions are scalable, high quality, and production ready.

For recruiter to interpret accurately

Not a pure data analyst this is an engineering-focused ML/GenAI role

Not theoretical AI requires real-world deployment experience

Strong fit for candidates with backgrounds in:

• ML Engineering
• Applied Data Science
• GenAI / LLM application development

Key Responsibilities

Design and implement AI/ML solutions using Python and modern ML frameworks

Develop and optimize Prompt Engineering strategies for LLM-based systems

Build and deploy Retrieval-Augmented Generation (RAG) pipelines

Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications

Develop and orchestrate Agentic AI workflows with tool/function calling

Implement vector search solutions using Vector Databases

Ensure CI/CD integration and cloud deployment (Azure preferred)

Establish observability, monitoring, and evaluation frameworks for AI systems

Collaborate with cross-functional teams to deliver production-ready AI features

Generic Managerial Skills, If any

Ability to explain complex ML / GenAI concepts to non technical stakeholders and collaborate effectively with cross functional teams.

Strong analytical thinking to break down ambiguous business problems into workable ML or GenAI solutions.

Takes end to end responsibility for solutions-from design to production readiness-without constant supervision.

Works well with data engineers, product owners, and platform teams to deliver integrated, scalable solutions.

Actively keeps up with evolving ML, LLM, and GenAI technologies and improves skills proactively.

AI/ML Engineer location : Woodlands CA