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.

Roles & Responsibilities :

- 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