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AIML Engineer
Job Location:
Job Location:
Woodland Hills, CA - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
30 July 2026 (30+ days ago)
Posted:
Application Deadline:
27 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Skill set
Python (Expert level) Machine Learning & Model Training o Training evaluation fine-tuning o Tagging and labeling workflows Generative AI & LLMs o Prompt engineering for LLM-based applications Document Processing o Document extraction parsing and chunking o Handling structured & unstructured data Embeddings & Vector Search o Embedding generation o Vector database integration Databases o Vector Databases o MongoDB Production-grade ML Engineering o Scalable production-ready ML/GenAI solutions
Roles & Responsibilities
This role is for a hands-on AI/ML Engineer who will design build and deploy productiongrade 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.
Python (Expert level) Machine Learning & Model Training o Training evaluation fine-tuning o Tagging and labeling workflows Generative AI & LLMs o Prompt engineering for LLM-based applications Document Processing o Document extraction parsing and chunking o Handling structured & unstructured data Embeddings & Vector Search o Embedding generation o Vector database integration Databases o Vector Databases o MongoDB Production-grade ML Engineering o Scalable production-ready ML/GenAI solutions
Roles & Responsibilities
This role is for a hands-on AI/ML Engineer who will design build and deploy productiongrade 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.
