AI/ML Developer

Role Overview

We are seeking a highly skilled Senior AI/ML Developer to design, architect, and deliver enterprise-grade Generative AI solutions , with a strong focus on healthcare use cases . The ideal candidate will combine deep technical expertise in machine learning, large language models (LLMs), and software engineering to build scalable, secure, and responsible AI systems.

Key Responsibilities

AI/ML Development & Architecture

• Design and develop scalable AI/ML solutions using LLMs and other machine learning models .
• Architect and implement Generative AI systems that are scalable, resilient, and aligned with ethical AI practices.
• Work as a Subject Matter Expert (SME) for Generative AI, partnering with Product and Engineering teams.
• Develop and maintain end-to-end AI pipelines , including:
• Data preprocessing
• Feature engineering
• Model training and evaluation

Solution Design & Integration

• Build extensible APIs and integrations to connect AI models with enterprise systems.
• Develop low-code/no-code UI/UX solutions for rapid delivery cycles.
• Design structured outputs (JSON, arrays, HTML) with nested nodes , ensuring seamless frontend/dashboard consumption .
• Implement solutions integrating LLMs (e.g., GPT models) to extract insights and deliver actionable data.

Cloud & Distributed Systems

• Architect and deploy solutions on cloud platforms such as AWS, Azure, or GCP.
• Build and maintain distributed, scalable systems for AI workloads.
• Optimize models and systems for performance, scalability, and efficiency .

AI Optimization & Prompt Engineering

• Optimize generative AI models for improved accuracy and response quality.
• Develop effective prompt engineering strategies based on understanding how AI interprets data.
• Implement advanced use cases such as:
• Retrieval-Augmented Generation (RAG)
• Conversational systems
• Summarization and translation

Responsible AI & Governance

• Design solutions aligned with Responsible AI principles :
• Fairness
• Transparency
• Security
• Accountability
• Identify, assess, and mitigate risks associated with generative AI systems .
• Ensure compliance with privacy and data protection standards , especially in healthcare environments.

Collaboration & Documentation

• Collaborate closely with cross-functional teams including Product, Data, and Engineering.
• Translate business problems into actionable AI-driven solutions .
• Create clear documentation:
• Technical specifications
• Architecture diagrams
• User guides and presentations
• Contribute to best practices and standards for AI/ML development across the organization.

Required Qualifications

• Proven experience delivering at least one large-scale Generative AI solution .
• Strong hands-on experience with:
• Machine Learning & AI (especially NLP and Generative AI)
• Frameworks: TensorFlow, PyTorch
• Open-source platforms: Hugging Face
• Experience working with:
• LLMs (GPT family, DALL·E, or similar)
• Data pipelines and ML lifecycle management
• Strong software engineering skills for deploying AI into production environments.
• Experience building APIs, system integrations, and scalable architectures .
• Solid understanding of distributed systems design .

Preferred Qualifications

• Experience in healthcare domain or regulated environments.
• Hands-on experience with:
• RAG architectures
• AI-powered dashboards and visualization tools
• Familiarity with CI/CD and DevOps practices .
• Experience designing enterprise-grade, production-ready AI systems .

Technical Skills

• Programming: Python (preferred), SQL
• AI/ML: NLP, LLMs, Generative AI
• Frameworks: TensorFlow, PyTorch
• Tools: Hugging Face, APIs, data pipelines
• Cloud: AWS, Azure, GCP
• Data formats: JSON, HTML, structured outputs
• Version control: Git

Soft Skills

• Strong analytical and problem-solving abilities
• Excellent communication skills (technical and non-technical audiences)
• Ability to work in fast-paced, agile environments
• Strategic thinking and solution-oriented mindset