ML Engineering Data Science

HCL Global Systems, Inc.

$120K — $150K *
Enterprise Technology
11 - 15 years of experience
Job Overview by Ladders

Qualifications

  • 12+ years in Data Science Engineering, focusing on scalable ML and Generative AI solutions
  • 6+ years hands-on experience with Python, including model training and document processing
  • 6+ years expertise with vector databases and modern ML/GenAI frameworks
  • 6+ years of experience building LLM-based applications and document pipelines
  • 6+ years implementing embedding generation and vector search solutions
  • Strong understanding of ML algorithms and Generative AI concepts

Responsibilities

  • Develop and deploy ML and Generative AI solutions using Python
  • Design prompt engineering strategies for LLM applications
  • Build pipelines for document extraction, parsing, and chunking
  • Train and fine-tune ML models while managing workflows
  • Implement vector search solutions and embedding generation
  • Integrate ML models with Vector Databases and MongoDB
  • Ensure code quality, scalability, and production readiness

Benefits

  • Hybrid work option
  • Involvement in innovative ML and Generative AI projects
  • Opportunity for professional growth and skill advancement
  • Engagement with cutting-edge technologies
  • Collaborative team environment
Full Job Description
Role: ML Engineering Data Science
Location - Woodland Hills, CA (Hybrid)

Must Have Skills
Skill 1 - Yrs of Exp - 12+ - Data Science Engineer to design and develop scalable ML and Generative AI solutions.
Skill 2 - Yrs of Exp - 6+ - Python, hands-on experience in model training, document processing pipelines.
SKill 3 - Yrs Of Exp - 6+ - vector databases and modern ML/GenAI frameworks, deploy machine learning and GenAI solutions using Python Design
SKill 4 - Yrs Of Exp - 6+ - LLM-based applications Build document extraction, parsing, and chunking pipelines for structured and unstructured data Train, evaluate, and fine-tune ML models
Skill 5 - Yrs of Exp - 6+ - workflows Implement embedding generation and vector search solutions Integrate ML models with Vector DBs and MongoDB Ensure code quality, scalability, and production readiness
Skill 6 - Yrs of Exp - 6+ - Solid understanding of ML algorithms and Generative AI concepts Experience working with Vector Databases and/or MongoDB

Job Title: Lead II - ML Engineering Data Science Engineer Role Overview 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. 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 Required Qualifications Expert-level proficiency in Python Strong experience in 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 working with Vector Databases and/or MongoDB

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