Job Title : ML Engineer
Experience : 9+ Years
Location : Bangalore (On-site – 5 Days a Week)
Employment Type : Full-Time
About the Role :
We are looking for a highly experienced and driven ML Engineer with a strong background in Generative AI, Large Language Models (LLMs) , and machine learning systems . This is a critical role where you will help design, build, and optimize advanced AI / ML solutions that power intelligent products and platforms.
As a senior member of the AI team, you will work on state-of-the-art NLP models, contribute to the architecture of GenAI systems, and bring research to production in a fast-paced and collaborative environment.
Key Responsibilities :
- Design and implement scalable AI / ML models, with a focus on LLMs and Generative AI use cases.
- Fine-tune and deploy foundation models (e.g., GPT, LLaMA, Mistral) using Python and modern ML frameworks.
- Lead research, experimentation, and prototyping of new ML algorithms and NLP approaches.
- Collaborate with data scientists, MLOps engineers, and product teams to integrate AI capabilities into real-world applications.
- Develop APIs and end-to-end ML pipelines for training, testing, and deployment.
- Stay current with emerging trends in artificial intelligence and apply best practices in production environments.
Required Skills :
9+ years of experience in Artificial Intelligence , Machine Learning , and Python programming .Hands-on expertise in Generative AI and Large Language Models (LLMs) .Strong knowledge of frameworks such as PyTorch , TensorFlow , and Hugging Face Transformers .Experience with prompt engineering, fine-tuning, and inference optimization of LLMs.Solid understanding of NLP, deep learning architectures, and model performance evaluation.Experience working with vector databases (FAISS, Pinecone) and retrieval-augmented generation (RAG) architectures.Proven ability to translate complex research into scalable applications.Good to Have :
Exposure to LangChain , OpenAI APIs , Anthropic Claude , or other commercial LLM ecosystems.Familiarity with cloud platforms (AWS / GCP / Azure) and MLOps practices (Docker, MLFlow, CI / CD).Prior experience mentoring junior engineers or leading AI project teams.Contributions to open-source AI projects or published research in the AI / ML domain.