Machine Learning Engineer

Company: Quadrant Technologies

Website: Visit Website

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Business Type: Small/Medium Business

Company Type: Product & Service

Business Model: B2B

Funding Stage: Seed

Industry: Information Technology

Job Description We are seeking a highly skilled Machine Learning Engineer with hands-on experience in Large Language Models (LLMs) and Generative AI technologies. The ideal candidate will have expertise in building, fine-tuning, and deploying LLM-based solutions, along with strong programming skills and a deep understanding of modern AI frameworks and architectures.

This role requires a strong analytical mindset, excellent problem-solving capabilities, and the ability to evaluate and recommend the most effective approaches, models, and frameworks for diverse business use cases.

Key Responsibilities

• Design, develop, fine-tune, and deploy LLM-powered applications and solutions.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases.
• Implement parameter-efficient fine-tuning techniques such as LoRA and QLoRA.
• Work with frameworks such as LangChain, LangGraph, and Hugging Face to develop scalable AI applications.
• Train, fine-tune, evaluate, and optimize foundation models and domain-specific LLMs.
• Develop and maintain model deployment pipelines and production-grade AI systems.
• Analyze business requirements and recommend appropriate AI/ML architectures and frameworks.
• Collaborate with cross-functional teams to design scalable and efficient AI solutions.
• Contribute to system design discussions and provide high-level architectural recommendations.

Required Skills

• Strong experience with Large Language Models (LLMs) and Generative AI.
• Hands-on expertise in LoRA, QLoRA, and LLM fine-tuning techniques.
• Experience building Retrieval-Augmented Generation (RAG) applications.
• Proficiency in LangChain, LangGraph, and Hugging Face ecosystem.
• Experience with LLM training, evaluation, and optimization.
• Strong programming skills in Python and/or Java.
• Experience with model deployment, inference optimization, and productionization.
• Understanding of vector databases, embeddings, and semantic search concepts.
• Strong problem-solving, analytical, and logical reasoning skills.
• Good understanding of system design, scalability, and distributed architectures.
• Ability to evaluate multiple technical approaches and select optimal solutions based on business requirements.

Preferred Qualifications

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of MLOps, CI/CD pipelines, and containerization technologies.
• Familiarity with AI observability, monitoring, and model performance optimization.
• Experience building enterprise-grade GenAI applications.