AI/ML Engineer

VMC Soft Technologies, Inc; Bengaluru Urban; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

VMC Soft Technologies, Inc. in India seeks an AI/ML Engineer to develop and deploy classical ML and LLM-based solutions for business use cases. You will design prompts, RAG pipelines, and conduct model evaluation and experiment design, collaborating with cross-functional teams.

The role requires proficiency in Python, ML libraries, and modern AI tooling, with a focus on responsible AI and model documentation.

Qualifications

• Experience in building ML/LLM based solutions for business use cases.
• Proficiency with Python data libraries and ML frameworks.
• Hands-on experience with model evaluation metrics and responsible AI.
• Familiarity with RAG pipelines and prompt engineering.

Responsibilities

• Develop and deploy classical ML and LLM-based solutions.
• Design prompts and RAG pipelines.
• Evaluate models using AI/ML metrics.
• Conduct experiment design and model validation.
• Create Model Cards and documentation.
• Collaborate with business and engineering teams.

Skills

Classical Machine Learning

LLM Development

Prompt Engineering

Retrieval-Augmented Generation

Experiment Design

AI/ML Evaluation Metrics

Model Cards & Responsible AI

Python

Scikit-learn

Pandas

NumPy

Tools

TensorFlow

PyTorch

Hugging Face

LangChain

LlamaIndex

Vector Databases

FAISS

ChromaDB

Pinecone

MLflow

Docker

Kubernetes

FastAPI

REST APIs

Azure AI

AWS SageMaker

Vertex AI

Job description

AI/ML Engineer Short JD

Job Title:

AI/ML Engineer

Experience:

4 8 Years

Location:

Chennai / Bangalore / Pune / Hyderabad

Job Summary

Looking for an AI/ML Engineer with experience in Classical Machine Learning, Large Language Models (LLMs), Prompt Engineering, RAG, Model Evaluation, and Experiment Design. The candidate should be capable of developing, evaluating, and optimizing AI/ML solutions for business use cases.

Must-Have Skills

Classical Machine Learning LLM Development & Evaluation Prompt Engineering Retrieval-Augmented Generation (RAG) Experiment Design AI/ML Evaluation Metrics (Accuracy, Precision, Recall, F1, ROC-AUC, BLEU, ROUGE) Model Cards & Responsible AI Python, Scikit-learn, Pandas, NumPy

Good-to-Have Skills

TensorFlow / PyTorch Hugging Face LangChain / LlamaIndex Vector Databases (FAISS, ChromaDB, Pinecone) MLflow Docker / Kubernetes FastAPI / REST APIs Azure AI / AWS SageMaker / Vertex AI

Responsibilities

Develop and deploy classical ML and LLM-based solutions. Design prompts and RAG pipelines. Evaluate models using AI/ML metrics. Conduct experiment design and model validation. Create Model Cards and documentation. Collaborate with business and engineering teams.