Senior AI Engineer

Budget: $8 - $15/hr

We are looking for one senior, hands-on AI professional who can independently own and execute multiple AI workstreams end to end. This is a single requirement, not multiple specialist roles.

The person should be strong across modern AI engineering and capable of taking problems from architecture and prototyping through optimization, deployment, and production readiness. The work may span LLMs / SLMs, recommendation engines, agentic interview workflows, AI-based result assessments, multimodal AI systems, classical ML, deep learning, and MLOps.

This role is best suited for someone who is a strong AI generalist with solid engineering discipline and the ability to convert ambiguous problem statements into practical, scalable AI systems. The source role requires 5+ years of experience entirely in the AI/ML domain.

What You Will Work On - Design and build AI solutions across multiple use cases and workstreams Develop and optimize LLM / SLM applications, including prompt engineering, fine-tuning, adapters, retrieval workflows, and production inference pipelines Build recommendation / ranking / matching systems using strong applied ML foundations Create agentic interview workflows and related orchestration logic Build AI-based assessment and result evaluation pipelines with measurable quality and consistency Work on multimodal AI systems where relevant Build prototypes and convert them into production-ready systems Create reusable AI components, tools, and frameworks Support end-to-end AI system design across training, inference, monitoring, and lifecycle management Contribute to deployment reliability, reproducibility, CI/CD practices, and model monitoring

Required Skills - 5+ years of experience in the AI/ML domain Strong Python skills Strong experience with AI/ML frameworks such as PyTorch, TensorFlow, or JAX Experience with LLM fine-tuning, prompt engineering, adapters, RAG, vector databases, and multimodal pipelines Strong grounding in classical ML, deep learning, NLP, CV, applied ML, and MLOps Experience deg end-to-end AI systems from training to inference to monitoring Experience with APIs, microservices, cloud platforms, and containers Strong problem-solving ability, communication, and ownership mindset

Preferred - Experience building internal AI tools or reusable AI platforms Experience with AI evaluation frameworks, production guardrails, or safety-oriented workflows Experience with agent-based or AI automation systems Experience with distributed training or GPU / accelerator optimization

Engagement Type/Open to - Freelancer Contractor Consultant Engineer Full-time, for the right candidate

Location Preference - Magarpatta City, Pune Preferred working model - Work from office for any of the above engagement types.

When Applying, Please Share - Relevant project examples in LLMs / SLMs / recommendation systems / AI agents / AI assessments / multimodal AI / MLOps Your exact role in those projects Tech stack used Whether you are open to working from Magarpatta City, Pune Your preferred engagement model: Freelancer / Contractor / Consultant Engineer / Full-time