AI Engineer - Machine/Deep Learning

Role Overview :

As an AI Engineer, you will design, build, and deploy AI/ML solutions across VTION.ai's products and data platforms. You will work closely with Product, Data Science, Engineering, and Business teams to identify opportunities where AI can improve data intelligence, automation, decision-making, and user experience. The role will involve working with LLMs, Generative AI, NLP, machine learning models, embeddings, RAG pipelines, and AI-powered applications.

Key Responsibilities :

• Design, develop, and deploy AI/ML solutions for VTION.ai's products and platforms.

• Build and integrate LLM-powered applications using models such as GPT, Claude, Gemini, or open-source LLMs.

• Develop RAG (Retrieval-Augmented Generation) pipelines, semantic search, embeddings, and vector-based solutions.

• Work on NLP and text intelligence use cases such as classification, summarization, sentiment analysis, entity extraction, and content understanding.

• Develop AI-powered features that leverage VTION's consumer and behavioral datasets.

• Build and optimize AI pipelines for large-scale data processing and inference.

• Experiment with different models, prompts, architectures, and approaches to improve accuracy, latency, and cost.

• Fine-tune or adapt models where required for specific business use cases.

• Develop APIs and services to integrate AI capabilities into existing products.

• Collaborate with Product and Engineering teams to take AI solutions from POC to production.

• Monitor model performance, reliability, latency, and cost in production.

• Implement appropriate evaluation frameworks to measure the quality and accuracy of AI outputs.

• Stay updated with developments in Generative AI, LLMs, Agentic AI, NLP, and emerging AI technologies.

Required Skills & Experience:

• 2 - 4 years of experience in AI/ML Engineering, Machine Learning, Data Science, or a related field.

• Strong programming skills in Python.

• Hands-on experience with LLMs and Generative AI applications.

• Experience with frameworks/libraries such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or equivalent.

• Strong understanding of Machine Learning and Deep Learning fundamentals.

• Experience working with NLP, embeddings, vector databases, and RAG architectures.

• Experience building and consuming REST APIs and integrating AI models into applications.