Walk-in || Generative AI Engineer- Blackstraw.ai- Chennai

About the Role

We are looking for a Generative AI Engineer who can design, develop, and implement advanced AI models and solutions that leverage large language models (LLMs), diffusion models, and multimodal AI systems. The ideal candidate should have a strong background in machine learning, deep learning, and prompt engineering, along with hands-on experience in deploying GenAI solutions at scale.

Key Responsibilities

• Develop and fine-tune generative models (e.g., GPT, LLaMA, Claude, Stable Diffusion) for text, image, audio, or video generation.
• Design and build end-to-end GenAI pipelines, from data collection and preprocessing to model training, evaluation, and deployment.
• Integrate LLMs and multimodal AI models into production systems using frameworks like LangChain, LlamaIndex, or OpenAI APIs.
• Conduct RAG (Retrieval-Augmented Generation) implementations for enterprise use cases.
• Collaborate with cross-functional teams (data science, product, and engineering) to design intelligent AI-driven applications.
• Stay current with the latest AI research, tools, and frameworks to drive innovation.
• Optimize model inference, cost efficiency, and response latency.

Required Skills & Qualifications

• Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field.
• 3+ years of experience in ML/DL engineering with at least 2+ years in Generative AI applications.
• Strong knowledge of Python and ML frameworks such as PyTorch or TensorFlow.
• Experience with LLMs (e.g., OpenAI, Anthropic, Mistral, LLaMA) and open-source libraries (LangChain, Hugging Face Transformers, etc.).
• Understanding of prompt engineering, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate, Milvus).
• Familiarity with cloud platforms (AWS, Azure, or GCP) and MLOps best practices.
• Strong problem-solving, research, and analytical skills.

Good to Have

• Experience with diffusion or image generation models (e.g., Stable Diffusion, Midjourney, DALL•E).
• Exposure to multimodal systems combining text, vision, and speech.
• Exposure to Azure services like Azure AI foundry, AI search etc.
• Knowledge of API development, containerization (Docker, Kubernetes), and CI/CD pipelines.
• Contributions to open-source AI projects or research publications in NLP/GenAI.

Key traits:

• Should have excellent communication skills.
• Should be self motivated and willing to work as part of a team.
• Should be able to collaborate and coordinate with team members onshore and offshore.
• Be a problem solver and be proactive to solve the challenges that come his way.