Job Description :

We are looking for a Machine Learning & Generative AI Engineer with strong hands-on expertise in Python, Machine Learning, Deep Learning, NLP, and Generative AI. The ideal candidate will be responsible for developing, evaluating, and deploying intelligent ML/AI solutions, with a strong focus on LLM applications, RAG, prompt engineering, embeddings, and agentic workflows.

The role requires a combination of strong statistical and machine learning fundamentals along with practical experience building production-ready Generative AI applications.

Key Responsibilities :

- Design, develop, train, and evaluate machine learning and deep learning models using Python.

- Apply techniques in NLP, statistical modelling, experimentation, feature engineering, and model evaluation.

- Build and optimize ML pipelines for real-world business use cases.

- Develop Generative AI and LLM-powered applications.

- Design and implement Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases.

- Develop effective prompt engineering strategies for LLM-based applications.

- Work with LLM application frameworks such as LangChain, LlamaIndex, or equivalent.

- Build and evaluate agentic workflows and AI agents for complex tasks.

- Implement guardrails, safety mechanisms, and evaluation frameworks for LLM applications.

- Work with vector databases for efficient storage and retrieval of embeddings.

- Conduct experimentation and A/B testing to assess model and application performance.

- Monitor, evaluate, and continuously improve model accuracy, reliability, latency, and scalability.

- Collaborate with product, engineering, and data teams to translate business problems into AI/ML solutions.

- Stay updated with emerging developments in Generative AI, LLMs, NLP, and AI engineering.

Required Skills :

Machine Learning & Data Science :

- Strong proficiency in Python.

- Hands-on experience with Machine Learning and Deep Learning.

- Strong understanding of NLP concepts and techniques.

- Experience with statistical modelling and experimentation.

- Strong knowledge of feature engineering and model evaluation.

- Proficiency in SQL.

- Experience with scikit-learn.

- Hands-on experience with PyTorch or TensorFlow.

Generative AI / LLM :

- Hands-on experience with Generative AI and LLM application development.

- Strong expertise in Prompt Engineering.

- Experience building RAG-based applications.

- Understanding of embeddings and vector databases.

- Experience with LLM evaluation frameworks and evaluation methodologies.

- Experience implementing guardrails for LLM applications.

- Understanding of agentic AI workflows / AI agents.

- Experience with LangChain, LlamaIndex, or equivalent LLM application frameworks.

Good to Have :

- Experience working with multiple LLM providers/models.

- Knowledge of LLM fine-tuning, RAG optimization, or model adaptation techniques.

- Experience with cloud-based AI/ML platforms.

- Understanding of MLOps and model deployment practices.

- Experience taking AI/ML prototypes into production.

- Knowledge of observability, monitoring, and performance optimization for LLM applications.

Ideal Candidate :

- 3+ years of relevant experience in Machine Learning, Data Science, AI Engineering, or a related field.

- Strong programming and problem-solving capabilities.

- Strong combination of traditional ML + Generative AI/LLM expertise.

- Hands-on approach with the ability to build solutions from experimentation through production.

- Comfortable working in a remote and collaborative environment.

- Strong analytical mindset with a focus on experimentation, evaluation, and continuous improvement.