Location: Pune — On-site
Experience: 7+ years in software engineering, AI/ML, and systems architecture
Compensation: Equity-based, with performance-linked milestones
About the Role
NeuraMach AI builds AI products across education, language, creative content, energy, and financial analytics — all on AWS. We need one senior engineer to own the AI/ML layer end-to-end: research, training, deployment, and monitoring across our whole portfolio. This is a hands-on, in-office role — you'll be pairing, training models, and shipping code daily, not just advising.
What You'll Own
- AI/ML Engineering: Train, fine-tune, and evaluate models across LLM/RAG, generative, time-series, computer vision, and anomaly detection use cases. Own prompt engineering, agent design, and MCP server integrations.
- MLOps: Build training-to-production pipelines — experiment tracking, model registries, versioning, safe rollouts, and evaluation/drift monitoring.
- AWS Infrastructure: Own the cloud foundation across compute, storage, networking, AI/ML services (SageMaker, Bedrock), data pipelines, and observability.
- Backend & Integration: Own FastAPI/Celery/ValKey backend services and the integration layer connecting AI/ML, databases (Postgres/pgvector, DynamoDB), and the React/Next.js frontend.
- Team Leadership: Mentor a lean AI/ML and full-stack team through daily code reviews and hands-on unblocking; translate product strategy into technical roadmaps.
What We're Looking For
- 7+ years in engineering, with experience leading a pod or technical track
- Strong ML fundamentals and hands-on training experience (deep learning, NLP, CV, time-series, etc.), not just calling libraries
- Production LLM/RAG experience, with MCP fluency
- Hands-on MLOps and deep AWS proficiency (production experience across 15+ services)
- Strong backend skills: FastAPI, Celery, ValKey/Redis
- Comfortable reviewing React/Next.js code and making full-stack architecture calls
- Strong Python across ML, backend, and scripting
Nice to have: multi-domain model experience, multilingual NLP, IoT/streaming pipelines, EdTech/adaptive-learning background, AWS certifications.
Why Join
Real equity, full technical ownership (no micro-management), ground-floor impact on a live multi-domain AI product portfolio.
How to Apply
Email [email protected] with your résumé/LinkedIn, an AI/ML system you took to production, the hardest AWS/architecture problem you've solved, and your availability to work on-site from Pune.
Pay: ₹407,572.57 - ₹1,000,000.00 per year
Work Location: In person
