Data Science Engineer (ML Generative AI)
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Job Location:
Burbank, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
16 hours ago
Vacancies:
1 Vacancy
Job Summary
Position: Data Science Engineer (ML / Generative AI)
Location: Burbank CA***Day 1 Onsite***
Duration: 1 YearsTechnical Skills:
Advanced Python development for ML/AI workloads
End to end ML lifecycle: model training evaluation fine tuning and labeling/tagging workflows
Generative AI systems design including LLM-based application development
Prompt engineering optimization for large language models
Document AI pipelines: OCR/extraction parsing normalization and text chunking for structured & unstructured data
Embedding generation pipelines for semantic search and retrieval
Vector similarity search implementation using vector databases
ML model integration with Vector DBs and MongoDB
Production grade ML engineering: scalable maintainable and deployment ready code
Python Large Language Models (LLMs) (via LLM based applications) Vector Databases MongoDB
Roles & Responsibilities
We are seeking a highly skilled Data Science Engineer to design and develop scalable ML and Generative AI solutions. The ideal candidate will have deep expertise in Python hands-on experience in model training document processing pipelines and strong knowledge of vector databases and modern ML/GenAI frameworks.
Strong fit if the candidate:
Has expert-level Python skills
Has hands-on experience building ML/GenAI systems not just theoretical knowledge
Has worked on end-to-end ML pipelines (data model deployment)
Has experience with document AI embeddings and vector search
Thinks like an engineer (scalable maintainable production-ready code)
Likely not a fit if the candidate is:
Primarily a BI / reporting analyst
Focused only on statistical modeling or academic research
Lacking experience with deployment pipelines or GenAI systems
Key Responsibilities
Develop and deploy machine learning and GenAI solutions using Python
Design and optimize prompt engineering strategies for LLM-based applications
Build document extraction parsing and chunking pipelines for structured and unstructured data
Train evaluate and fine-tune ML models; manage tagging and labeling workflows
Implement embedding generation and vector search solutions
Integrate ML models with Vector DBs and MongoDB
Ensure code quality scalability and production readiness
Role Descriptions: Data Science Engineer Role OverviewThe Data Science Engineer will develop scalable ML and Generative AI solutions specializing in model training document processing pipelines and vector search implementations. Strong Python expertise and experience across modern ML and GenAI workflows are Responsibilities- Develop and deploy Machine Learning and Generative AI solutions using Python- Design and refine prompt engineering strategies for LLM applications- Build document extraction parsing and chunking pipelines- Train evaluate and fine-tune ML models manage tagging and labeling workflows- Implement embedding generation and vector search solutions- Integrate ML models with vector databases and MongoDB- Ensure code quality scalability and production readinessRequired Qualifications- Expert-level proficiency in Python- Strong experience with model training evaluation and tagging workflows- Hands-on experience with document extraction and chunking techniques- Solid understanding of ML algorithms and Generative AI concepts- Experience with vector databases andor MongoDB
Essential Skills: Data Science Engineer Role OverviewThe Data Science Engineer will develop scalable ML and Generative AI solutions specializing in model training document processing pipelines and vector search implementations. Strong Python expertise and experience across modern ML and GenAI workflows are Responsibilities- Develop and deploy Machine Learning and Generative AI solutions using Python- Design and refine prompt engineering strategies for LLM applications- Build document extraction parsing and chunking pipelines- Train evaluate and fine-tune ML models manage tagging and labeling workflows- Implement embedding generation and vector search solutions- Integrate ML models with vector databases and MongoDB- Ensure code quality scalability and production readinessRequired Qualifications- Expert-level proficiency in Python- Strong experience with model training evaluation and tagging workflows- Hands-on experience with document extraction and chunking techniques- Solid understanding of ML algorithms and Generative AI concepts- Experience with vector databases andor MongoDB
Desirable Skills:
Keyword:
Skills: Digital : Machine LearningDigital : Mongo DBDigital : Python for Data ScienceGenerative AI
Experience Required: 10 & Above
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
