Artificial Intelligence Engineer

AI Engineer Machine Learning, Generative & Applied Systems

Location: Chennai / Erode

Company: Indovation Lab

Experience Level: Overall exp 5 + Years, Relevant exp 3+ (Multiple levels open)

Type: Full-time | Product + Research + Applied AI

About the Role

We are on a mission to build the next generation of AI-driven systems — intelligent, context-aware, and capable of reasoning, speaking, seeing, and acting.

Our AI Engineering team blends research, experimentation, and production engineering to deliver high-performance, real-world AI products.

We're looking for hands-on AI Engineers who can move fluidly between model development, LLM orchestration, and multi-modal AI integration.

Whether your strength lies in classical ML, deep learning, LLMs and conversational systems, or applied voice and vision AI, this role offers the opportunity to work on frontier problems that touch millions of users.

You'll collaborate closely with product, data, and engineering teams to design, build, and deploy AI systems that learn, reason, and interact naturally with humans.

Who You Are

You are an AI builder — part researcher, part engineer. You've moved beyond experiments and notebooks and have built or deployed at least one system that's powered by AI in production.

You're comfortable with both the math and the machinery, and you thrive in the space where innovation meets practical engineering.

You might have started as a data scientist, ML engineer, or full-stack developer who fell in love with AI — and now you're looking for a role that lets you design, scale, and productize intelligence.

Key Focus Areas (Choose Your Track)

We welcome candidates across four interconnected disciplines of AI Engineering. You may specialize in one or span multiple tracks:

Category

You'll Excel Here If You...

Example Projects You'll Build

1 Core Machine Learning

Love solving structured data problems, building predictive models, and applying statistical learning.

Predictive analytics, feature pipelines, anomaly detection, customer scoring, explainable models.

2 Deep Learning & Neural Networks

Are passionate about designing architectures and optimizing model performance on GPUs.

CNNs for vision tasks, Transformers for embeddings, model pruning/quantization, distributed training.

3 NLP, LLMs & Conversational AI

Thrive on designing AI that can read, reason, and respond — you understand prompt design, context windows, and retrieval logic.

Fine-tuning GPT/LLaMA, building LangChain/RAG apps, designing multi-turn dialogue flows, LLM integration with APIs.

4 Applied AI – Voice, Vision & Agentic Systems

Enjoy working on end-to-end AI systems that interact with the world — from voicebots to autonomous multi-agent pipelines.

Real-time STTLLMTTS systems, visual reasoning (YOLO/OpenCV), multi-modal AI assistants, LangGraph agents.

Your Core Responsibilities

Depending on your background, you will:

• Design, build, and train ML/LLM models tailored to business or product use-cases
• Develop and fine-tune pipelines — from data ingestion to model deployment
• Experiment with open-source models (LLaMA, Mistral, Falcon, Claude, etc.) and adapt them to specific tasks
• Build multi-agent AI systems that combine reasoning, memory, and tool use
• Integrate Speech/Vision AI — build real-time voicebots, text understanding, or object detection systems
• Deploy scalable AI systems with proper monitoring, versioning, and latency management
• Collaborate cross-functionally with data engineers, software developers, and designers to make AI usable, measurable, and explainable

Our Tech Ecosystem

Area

Frameworks / Tools

Languages & Frameworks

Python, C++, JavaScript, FastAPI, Flask

Core ML & Deep Learning

PyTorch, TensorFlow, Scikit-learn, XGBoost, Keras, LightGBM

LLMs & GenAI

LangChain, LangGraph, HuggingFace, CrewAI, LLaMA, GPT, Mistral, Falcon

Speech & Voice AI

Whisper, Deepgram, NeMo, ElevenLabs, Coqui, AWS Polly

Computer Vision

YOLOv8, OpenCV, ViT, SAM, Detectron2, GR00T, Stable Diffusion

Vector Databases & Retrieval

FAISS, Pinecone, ChromaDB, Redis

Infrastructure & MLOps

AWS, GCP, Azure, MLflow, Docker, Kubernetes, Weights & Biases, GitHub Actions

You'll Be Great Here If You...

• Think like a builder — you're not afraid of messy data or incomplete models
• Understand the trade-offs between open-source vs. proprietary models
• Can design for scale — low latency, distributed training, multi-agent orchestration
• Write clean, modular, production-quality code
• Are comfortable learning, experimenting, and documenting
• Believe that AI is not just about intelligence, but impact — measurable, human-centered outcomes

Our Ideal Candidate Has

• Bachelor's or Master's in Computer Science, Engineering, Data Science, or related field
• 3+ years of Project experience in AI/ML development (ML Engineer, AI Engineer, or Research role)
• Hands-on experience with LLMs, neural networks, or applied AI systems
• Prior exposure to cloud deployment and vector database usage
• Familiarity with evaluation metrics, model optimization, and inference design

Why Join Us

• Build AI that ships — not research stuck in slides
• Work across LLMs, speech, and vision, not just one domain
• Collaborate with industry leaders and applied researchers
• Experiment with the latest open-source and frontier AI models
• Opportunity to own full AI pipelines — from data to product delivery
• Flexible work structure, strong mentorship, and clear growth path toward Senior / Principal AI Engineer roles