Role
Overview

You
will be involved in full lifecycle AI solution delivery – from research and
prototyping to scaling and deployment. The ideal candidate combines robust
theoretical ML/DL grounding with applied experience in foundation models, LLM
fine-tuning, vector search, Gen AI application frameworks, and deployment on
large-scale infrastructure.

Key
Responsibilities

· Architect, build, and deploy Generative AI solutions
tailored to business problems.

· Fine-tune and customize foundation/LLM models (e.g.,
GPT, LLaMA, Mistral, Falcon, Claude, Gemma).

· Build LLM-powered applications using frameworks such
as LangChain, Haystack, LlamaIndex.

· Develop and manage RAG (Retrieval Augmented
Generation) pipelines integrating vector databases (FAISS, Pinecone, Weaviate,
Milvus, ChromaDB).

· Work with cloud AI services such as Azure OpenAI, AWS
Bedrock, SageMaker, GCP Vertex AI.

· Implement MLOps pipelines for model
training/monitoring using tools like MLflow, Kubeflow, Weights & Biases,
DVC.

· Leverage Hugging Face ecosystem (Transformers,
Diffusers, PEFT, Datasets)



for model experimentation.

· Optimize AI workflows with GPU acceleration and
inference optimization (e.g., ONNX, TensorRT, DeepSpeed, vLLM).

· Design and enforce secure, ethical, and responsible AI
practices in all deployments.

· Collaborate with consultants, data engineers, and
business analysts to understand client problems and deliver measurable
solutions.

· Mentor junior engineers; contribute to internal
accelerators and reusable solution templates.

Requirements
Required
Qualifications

· Education: Bachelor’s/Master’s in Computer Science,
Data Science, AI/ML, or a related field.

· Experience: 5+ years in ML/DL, with minimum 2 years in
Generative AI solution development.

· Expertise with Python and ML/DL libraries (PyTorch,
TensorFlow, JAX).

· Strong knowledge of LLM training/fine-tuning
techniques: LoRA, QLoRA, PEFT, instruction tuning.

· Proficiency in prompt engineering

📌 Gen AI Engineer (Bengaluru)
🏢 Thoucentric
📍 Bengaluru