Machine Learning Engineer

Humanli.AI is a Startup founded by Alumnus of IIM' Bangalore/ISB Hyderabad & IIM' Calcutta. We are democratizing and extending technology that were accessible & consumed only by MNC’s or Fortune companies to SME and Mid-size firms. We are pioneers in bringing Knowledge Management algorithms & Large Language Models into Conversational BOT framework.

Job Title: AI/ML Engineer

Location: Jaipur

Job Type: Full-time

Experience: 0-3 years

We are looking for an experienced AI/ML & Data Engineer to join our team and contribute to the development and deployment of our AI-based solutions. As an AI/ML & Data Engineer, you will be responsible for designing and implementing data models, algorithms, and pipelines for training and deploying machine learning models.

Responsibilities:

Design, develop, and fine-tune Generative AI models (e.g., LLMs, GANs, VAEs, Diffusion Models).

Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases (FAISS, Pinecone, ChromaDB, Weaviate).

Develop and integrate AI Agents for task automation, reasoning, and decision-making.

Work on fine-tuning open-source LLMs (e.g., LLaMA, Mistral, Falcon) for specific applications.

Optimize and deploy transformer-based architectures for NLP and vision-based tasks.

Train models using TensorFlow, PyTorch, Hugging Face Transformers.

Work on prompt engineering, instruction tuning, and reinforcement learning (RLHF).

Collaborate with data scientists and engineers to integrate models into production systems.

Stay updated with the latest advancements in Generative AI, ML, and DL.

Optimize models for performance improvements, including quantization, pruning, and low-latency inference techniques.

Qualification:

B.Tech in Computer Science.

Fresher's may apply

0-3 years of experience in data engineering and machine learning.

Immediate joiners: Preferred

Requirement

Experience with data preprocessing, feature engineering, and model evaluation.

Understanding of transformers, attention mechanisms, and large-scale training.

Hands-on experience with, RAG, LangChain/LangGraph, LlamaIndex, and other agent frameworks.

Understanding of prompt tuning, LoRA/QLora, and efficient parameter fine-tuning (PEFT) techniques.

Strong knowledge of data modeling, data preprocessing, and feature engineering techniques.

Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.

Excellent problem-solving skills and ability to work independently and collaboratively in a team environment.

Strong communication skills and ability to explain technical concepts to non-technical stakeholders.