Artificial Intelligence Consultant

Description

Role : Lead AI / ML Developer

Experience : 8-11 Years

Location : Bengaluru

Job Description

Role

: Lead AI / ML Developer

Tech Stack

Python, Scikit Learn ,PyTorch ,LangChain , Postgress SQL, Transformers

Required Skills & Qualifications

Bachelor’s or master’s degree in computer science , Information Technology , or a related field.

8-11 years

of experience in software development, with at least

3+ years

in experience in AI / ML development

Expertise in :

Programming & ML Foundations :

Proficient in Python with extensive experience in major ML libraries, including TensorFlow, PyTorch, and Scikit-learn..

Natural Language Processing :

Skilled in leveraging NLP frameworks such as SpaCy, NLTK, and Hugging Face Transformers for text analysis and model development.

Deep Learning Architectures :

Strong understanding and practical application of CNNs, RNNs, LSTMs, and Transformer-based architectures.

Generative & Agentic AI :

Hands-on experience with Large Language Models (LLMs), LangChain, AutoGen, and Agentic AI frameworks with focus on memory management, vector search, embeddings, and Retrieval-Augmented Generation (RAG).

Machine Learning Operations (MLOps) :

Knowledgeable in end-to-end ML lifecycle management using MLflow, DVC, and Kubeflow; experienced in implementing CI / CD pipelines for AI / ML workflows.

Cloud & Deployment Expertise :

Skilled in deploying AI solutions on AWS SageMaker, Azure AI, and GCP AI Platform; proficient with AWS services and cloud integration.

Multi-Modal & Reinforcement Learning :

Familiarity with multi-modal AI systems and reinforcement learning methodologies.

DevOps :

Working knowledge of DevOps principles; Any certification considered an added advantage.

Excellent problem-solving, analytical, and communication skills.

Roles and Responsibilities

Develop and deploy AI / ML models across NLP, computer vision, and predictive analytics use cases.

Work with state-of-the-art LLMs (OpenAI, Gemini, Mistral, Llama) and agent frameworks (LangChain, Lang graph, CrewAI, AutoGen).

Design and Implementation of End to End -AI / ML -Architectural flows

Implementation and Optimise Deep Learning Model (CNN,RNN, Transformers)

Design and optimize conversational AI systems (chatbots, voice assistants) and recommendation engines.

Build AI-powered APIs and microservices using FastAPI or Flask.

Integrate vector databases (Pinecone, FAISS, Weaviate, Croma DB) for semantic search and RAG pipelines.

Apply fine-tuning, prompt engineering, and evaluation techniques for improved model performance.

Deploy and monitor AI solutions on cloud platforms (AWS, Azure, GCP) following MLOps best practices.

Collaborate with cross-functional teams to bring AI solutions into production at scale.

Notice period : Candidate has to join within a month (Mandatorily)