Job Description :
Job Title : AI / ML Engineer
Experience : 4+ Years
Location : Bangalore - Hybrid
Notice Period : Immediate Joiner
Job Role :
We are looking for skilled AI / ML Engineers with strong hands-on experience in LLMs, embeddings, and related frameworks. The ideal candidate should demonstrate practical expertise in at least 4-5 of the listed key skills. This role requires active involvement in building, fine-tuning, and deploying language and vision models, while working in a collaborative hybrid setup.
Responsibilities :
- Fine-tune and train Large Language Models (LLMs), Small Language Models (SLMs), and Vision Language Models (VLMs) using frameworks like Hugging Face, PyTorch, or TensorFlow
- Work on integrating LLMs with embeddings, transformers, and vector databases
- Build and manage MLOps pipelines and scalable data engineering workflows
- Apply techniques such as prompt tuning, prompt chaining, and agent-based approaches for solving real-world use cases
- Collaborate with data scientists, engineers, and product teams to deliver AI-driven solutions
- Deploy and monitor models in production environments
- Perform POCs and implement the best architectural choices for model deployment
Requirements :
4+ years of hands-on experience in AI / ML engineeringProficient in at least 4-5 of the following :
Fine-tuning LLMs / SLMs / VLMs using Hugging Face, PyTorch, TensorFlowEmbeddings, TransformersVector databases (e.g., FAISS, Pinecone)Prompt engineering (prompt tuning, chaining, agent-based models)MLOps & Data Engineering workflowsStrong Python programming skillsExperience in model deployment and performance optimizationSolid understanding of NLP and / or multimodal AI systemsLocation : Bangalore (Hybrid mode)Technical Skills :
Fine-tuning, LLMs, SLMs, VLMs, HuggingFace, PyTorch, TensorFlow, Embeddings, Transformers, VectorDBs, FAISS, Pinecone, MLOps, CI / CD, Deployment, Monitoring, DataOps, ETL, Prompting, Prompt-Tuning, Prompt-Chaining, Agents, Evaluation, Optimization, Python, APIs
(ref : hirist.tech)