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Clinical AI / Machine Learning Engineer

Actalent

Bengaluru / Hyderabad / Pune / Chennai

8+ years

Today

$62.7K–77.1K/yr

Full-time

Onsite

Skills Required

LLM

RAG

Gen AI

LLM Fine-tuning

LLM Evaluation

Machine Learning

AI

Clinical AI

Healthcare

LoRA

QLoRA

PEFT

Instruction Tuning

Domain Adaptation

Benchmarks

Description

Actalent is hiring a Clinical AI / Machine Learning Engineer to build production-grade AI systems for clinical use cases. The role emphasizes autonomous agents, multi-agent architectures, fine-tuning, and rigorous LLM evaluation for safe and scalable clinical AI products.

Company: Actalent

Role: Clinical AI / Machine Learning Engineer

Location: Bangalore, Karnātaka, India

Experience

- At least 8 years of hands-on AI and machine learning engineering experience
- Experience building, deploying, and maintaining AI systems in production
- Experience delivering at least one autonomous AI agent system on real data with tools and self-correction
- Experience integrating at least two large language models into production software
- Experience designing and implementing LLM evaluation pipelines and benchmarks
- Hands-on experience architecting multi-agent systems
- Solid software engineering skills for AI/ML production deployment, monitoring, and maintenance
- Background in clinical AI or healthcare-related AI/ML applications

Responsibilities

- Design, build, deploy, and maintain production-grade AI and machine learning systems for clinical use cases
- Develop and deploy autonomous AI agent systems on real-world clinical data




- Integrate multiple large language models into production environments
- Implement fine-tuning workflows for clinical AI models
- Design and manage LLM evaluation pipelines and continuous performance monitoring
- Architect multi-agent systems using orchestrator-worker patterns, tool-calling loops, and self-correcting pipelines
- Translate clinical and business requirements into AI engineering specifications and solutions
- Ensure robustness, reliability, and safety of AI systems in production
- Document system architectures, design decisions, and operational procedures
- Contribute to improvement of AI engineering practices, tools, and frameworks

Additional Responsibilities

- Work closely with cross-functional stakeholders, engineers, and other stakeholders to design and deploy AI solutions
- Support maintainability and knowledge sharing through documentation
- Troubleshoot production AI systems and drive iterative improvement
- Work in environments centered on advanced clinical AI and machine learning
- Build AI solutions that integrate LLMs and autonomous agents into clinical workflows
- Collaborate within a team focused on modern AI/ML tools and technologies

Nice To Have





- Experience with clinical AI and machine learning solutions
- Familiarity with clinical data and workflows
- Understanding of best practices for safe, reliable, and responsible LLM deployment in healthcare
- Ability to design and refine benchmarks that reflect real-world clinical performance requirements
- Strong communication skills to explain complex AI systems to technical and non-technical stakeholders
- Cooperative mindset and ability to work effectively in cross-functional teams

More Skills autonomous AI agents, multi-agent architectures, fine-tuning pipelines, evaluation frameworks, LLM evaluation pipelines, orchestrator-worker patterns, tool-calling loops, self-correcting agent pipelines, production deployment, monitoring, maintenance, clinical data, clinical workflows, Gemini, GPT-4, Llama, Mistral

Prepare for this role

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