Job Summary
IDEfforts Software Solutions is hiring its first AI/ML Engineer to lead AI development for our SaaS platform serving the trucking insurance industry. This is a founding AI role reporting directly to the CTO. You'll design and ship production AI systems — from document automation to predictive analytics — and shape the AI function from the ground up.
If you've built and deployed real ML/LLM systems (not just notebooks) and want true ownership, read on.
Key Responsibilities
- Design and build intelligent document processing pipelines using OCR, LLMs, and custom ML models for insurance documents (policies, claims, COIs, MVRs, loss runs).
- Develop AI-driven document funneling for routing, classification, and triage.
- Build predictive analytics models for risk scoring, claims forecasting, fraud detection, and user-facing insights.
- Fine-tune and deploy LLMs (LoRA, QLoRA, full fine-tuning) for domain-specific tasks.
- Build RAG systems end-to-end — embeddings, vector databases, retrieval pipelines, evaluation.
- Own the full ML lifecycle: data, modeling, deployment, monitoring, iteration.
- Set up MLOps infrastructure — experiment tracking, model versioning, CI/CD for ML.
- Make architectural decisions on models, frameworks, and build-vs-buy.
- Help grow and lead the AI team as the function expands.
Required Skills & Experience
- 3–6 years of hands-on experience building and deploying ML/AI systems in production.
- Strong proficiency in Python, PyTorch, and/or TensorFlow.
- Practical experience with LLMs — fine-tuning, prompt engineering, evaluation.
- Hands-on experience with Hugging Face Transformers.
- Built RAG systems with vector databases (Pinecone, Weaviate, pgvector, ChromaDB, or similar).
- Experience with LangChain, LlamaIndex, or equivalent LLM orchestration frameworks.
- MLOps experience: MLflow, Kubeflow, SageMaker, or similar tools.
- Cloud deployment experience on AWS, GCP, or Azure — GPU inference, autoscaling, cost optimization.
- Strong software engineering fundamentals: APIs, version control, testing, code review.
Preferred Qualifications
- Experience with Document AI — layout-aware models, OCR pipelines, form understanding (LayoutLM, Donut, etc.).
- Domain experience in insurance, fintech, logistics, or trucking.
- Strong classical ML skills (XGBoost, time-series forecasting) in addition to deep learning.
- Open-source contributions, ML/NLP publications, or notable side projects.
- Experience as an early/founding engineer at a startup.
Note: No formal degree requirement. We hire based on what you've built and shipped.
What We Offer
- Top-of-market compensation — no fixed budget ceiling for exceptional candidates.
- Founding AI role with direct CTO access and influence on product strategy.
- Dedicated GPU/compute budget for experimentation.
- Learning & development budget (courses, books, conferences).
- Opportunity to build and lead the AI team.
- Health insurance and standard statutory benefits.
How to Apply
Apply with your resume. In your application, please include:
- One AI/ML system you've built — what problem it solved, what shipped to production, and what you'd do differently today.
- Links to GitHub, portfolio, or published work (if available).
Key Skills
Artificial Intelligence, Machine Learning, Deep Learning, LLM, Large Language Models, Generative AI, GenAI, RAG, Retrieval Augmented Generation, NLP, Natural Language Processing, PyTorch, TensorFlow, Hugging Face, Transformers, LangChain, LlamaIndex, Vector Database, Pinecone, Weaviate, MLOps, MLflow, Kubeflow, SageMaker, AWS, GCP, Azure, Python, Document AI, OCR, Predictive Analytics, Fine-tuning, LoRA, QLoRA, Prompt Engineering
Pay: ₹2,200,000.00 - ₹2,800,000.00 per year
Benefits:
- Flexible schedule
- Leave encashment
- Paid sick time
- Paid time off
- Provident Fund
- Work from home
Work Location: Hybrid remote in Surat, Gujarat (Surat)
