Unify Technologies - Lead Machine Learning Engineer - LLM NLP

Employment Type : Full-Time

Role : Machine Learning Architect

Position : AI/ML Solutions Architect LLMs, Gen AI, NLP

Project : Advanced AI/ML Platforms Enterprise-Grade Solutions

Experience : 8+ Years

Key Skills : Machine Learning, LLMs, NLP, Generative AI, Python, Cloud Architecture, MLOps, Prompt Engineering

Number of Openings : 01

Joining Time : Immediate to 15 Days

Job Location : Gachibowli, Hyderabad India (Hybrid Work Mode)

Education : Masters/Bachelors degree in Computer Science, Artificial Intelligence, Engineering, or a related technical discipline preferred

Detailed Job Description

Key Qualifications :

• Minimum 8 years of experience in AI/ML with at least 2+ years in NLP, LLMs, and Generative AI.
• Proven expertise in ML architecture design, end-to-end model development, and deployment in production systems.
• Strong in Python with deep experience in ML libraries and frameworks such as TensorFlow, PyTorch, Hugging Face, and LangChain.
• Sound knowledge of transformer models, embeddings, tokenization, and vector databases (e.g., FAISS, Pinecone).
• Experience with cloud-native AI solutions on AWS, Azure, or GCP.
• Familiarity with MLOps, model versioning, containerization (Docker), and orchestration tools (e.g., Kubeflow, MLflow).
• Hands-on experience in designing and engineering prompts for LLMs to support use cases like summarization, classification, Q&A, and content generation.
• Strong understanding of retrieval-augmented generation (RAG) and techniques to combine structured/unstructured data with LLMs.
• Excellent problem-solving skills, architectural thinking, and ability to lead complex AI initiatives.
• Strong communication, stakeholder management, and technical leadership capabilities.
  
  

• Architect and implement scalable AI/ML solutions across multiple domains using modern ML, NLP, and Gen AI technologies.
• Design and develop LLM-powered applications, optimizing for prompt engineering, fine-tuning, and inference performance.
• Lead the design of AI pipelines and integrate ML components into production systems using MLOps and CI/CD practices.
• Evaluate and recommend LLM models (OpenAI, Cohere, Claude, LLaMA, etc.) based on performance, cost, and alignment with use cases.
• Collaborate with data scientists, ML engineers, and software teams to develop reusable ML components and foundational architectures.
• Drive model validation, A/B testing, and continuous monitoring of ML systems in production environments.
• Contribute to the development of an enterprise AI/ML platform that supports rapid experimentation and model lifecycle management.
• Lead initiatives on Gen AI strategy, security, and responsible AI practices.
• Mentor junior engineers and promote best practices in ML/AI development across the team.
• Stay up-to-date with emerging trends in LLMs, AI tooling, and open-source technologies