AI/ML Engineer

Northern Base; Alaska; On-site; USD 120,000 - 160,000; Full time

Job summary

Northern Base is seeking a hands-on AI/ML Engineer to design, build, and deploy production-grade ML and GenAI solutions.

The role centers on LLM-based applications, prompt engineering, document processing pipelines, and embedding-based search over structured and unstructured data. Proficient Python skills and end-to-end ML workflow delivery are essential.

Qualifications

• Proficient in Python with hands-on ML/GenAI experience.
• Experience in training, evaluation, and fine-tuning ML models.
• Prompt engineering for LLM-based applications.
• Document extraction, parsing, and chunking in production pipelines.
• Embedding generation and vector search; familiarity with vector databases.
• Experience with MongoDB in production ML contexts.
• Delivery of production-grade ML/GenAI solutions.

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) into enterprise applications.
• Develop and orchestrate Agentic AI workflows with tool calls.
• 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.

Skills

Python

ML Engineering

GenAI/LLMs

Prompt Engineering

Document Processing

Embeddings & Vector Search

Vector Databases

MongoDB

Production ML

Azure OpenAI

Tools

Azure OpenAI

CI/CD

Vector Databases

Job description

Role: AI/ML Engineer

Locations: Woodland Hills, CA/Mason,OH

Fulltime

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

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.

Strong fit for candidates with backgrounds in:

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