AI engineer

Job Description

This role is for one of the Weekday's clients

Salary range: Rs 2000000 - Rs 10000000 (ie INR 20 - 100 LPA)

Min Experience: 3 years

Location: India

JobType: full-time

We are seeking a skilled AI Engineer with 3–8 years of experience and a strong focus on Large Language Models (LLMs) to design, build, and optimize intelligent systems. This role is ideal for professionals who are passionate about advancing AI capabilities and applying LLMs to solve real-world business problems. You will work closely with cross-functional teams including product, data science, and engineering to develop scalable AI-powered applications.

Requirements

Key Responsibilities:

• Design, develop, and deploy applications leveraging LLMs for tasks such as text generation, summarization, classification, semantic search, and conversational AI.
• Fine-tune, prompt-engineer, and optimize LLMs to meet specific business requirements while improving accuracy, latency, and cost-efficiency.
• Build and maintain end-to-end ML pipelines, including data preprocessing, model training, evaluation, and deployment.
• Integrate LLM-based solutions into production systems via APIs and microservices.
• Implement retrieval-augmented generation (RAG) systems using vector databases and embeddings.
• Collaborate with stakeholders to translate business problems into AI-driven solutions.
• Monitor model performance in production and implement continuous improvement strategies.
• Stay up to date with advancements in LLMs, generative AI, and NLP research, and apply best practices.
• Ensure responsible AI practices, including bias mitigation, explainability, and data privacy compliance.

Required Skills & Qualifications:

• 3–8 years of experience in AI/ML engineering, with hands-on experience in NLP and LLMs.
• Strong programming skills in Python, with experience in frameworks such as PyTorch, TensorFlow, or JAX.
• Practical experience working with LLMs (e.g., GPT-style models, open-source LLMs) including fine-tuning and prompt engineering.
• Familiarity with libraries such as Hugging Face Transformers, LangChain, or similar ecosystems.
• Experience with vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding techniques.
• Solid understanding of machine learning fundamentals, deep learning architectures, and NLP concepts.
• Experience with cloud platforms (AWS, GCP, or Azure) and deploying scalable ML systems.
• Knowledge of REST APIs, microservices architecture, and containerization tools like Docker/Kubernetes.
• Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.

Preferred Qualifications:

• Experience with retrieval-augmented generation (RAG) and knowledge-grounded AI systems.
• Exposure to reinforcement learning from human feedback (RLHF) or model alignment techniques.
• Familiarity with MLOps tools and practices (CI/CD for ML, monitoring, versioning).
• Contributions to open-source AI/ML projects or research publications in NLP/AI.