LLM Engineer - NLP/Artificial Intelligence

Job Summary :

Key Responsibilities :

- Perform domain-specific adaptation and fine-tuning of foundation models using techniques like LoRA, PEFT, QLoRA, and prompt tuning.

- Collaborate with data engineers and domain experts to curate, preprocess, and label high-quality datasets for training and evaluation.

- Implement efficient training, evaluation, and deployment pipelines using frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, and LangChain.

- Optimize LLM inference and memory usage for scalability and latency reduction in production environments.

- Develop APIs and tools to serve LLM-powered applications in real time.

- Stay current with the latest research and advancements in NLP and LLMs and propose improvements or adoption of emerging techniques.

- Ensure responsible AI usage by incorporating fairness, safety, interpretability, and compliance

considerations.

Requirements :

Must-Have :

- Bachelors or Masters degree in Computer Science, AI, Machine Learning,

- 2- 5+ years of experience in machine learning or natural language processing.

- Hands-on experience working with LLMs (GPT-2/3/4, LLaMA, Mistral, Claude, PaLM, etc.).

- Strong programming skills in Python and experience with ML frameworks (e.g., PyTorch, HuggingFace Transformers, TensorFlow).

- Familiarity with prompt engineering, few-shot learning, retrieval-augmented generation (RAG), and model fine-tuning techniques.

- Experience with REST APIs, containerization (Docker), and ML Ops tools (e.g., MLflow, Weights & Biases).

- Good understanding of model evaluation metrics (BLEU, ROUGE, perplexity, hallucination detection).

Nice-to-Have :

- Exposure to privacy-preserving ML, model distillation, or federated learning.

- Familiarity with vector databases (Pinecone, Weaviate, FAISS) and embedding techniques.

- Experience with RLHF (Reinforcement Learning from Human Feedback).

- Contributions to open-source LLM projects or research publications.

Soft Skills :

- Excellent communication and documentation skills.

- Collaborative mindset and ability to work in fast-paced environments.

- Passion for AI/ML and a continuous learning attitude.