Senior AI Engineer
Budget: $8 – $15 USD
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 designing 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
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 designing 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