Tech Lead - AI/ML Engineer

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 HR@neuramach.ai with your rsum/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. Compensation: 407,572.57 - 1,000,000.00 per year Work Location: In person 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 HR@neuramach.ai with your rsum/LinkedIn, an AI/ML system you took to production, the hardest AWS/architectur