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
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Design and develop scalable AI/ML solutions using LLMs and other machine learning models .
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Architect and implement Generative AI systems that are scalable, resilient, and aligned with ethical AI practices.
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Work as a Subject Matter Expert (SME) for Generative AI, partnering with Product and Engineering teams.
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Develop and maintain end-to-end AI pipelines , including:
- Data preprocessing
- Feature engineering
- Model training and evaluation
Solution Design & Integration
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Build extensible APIs and integrations to connect AI models with enterprise systems.
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Develop low-code/no-code UI/UX solutions for rapid delivery cycles.
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Design structured outputs (JSON, arrays, HTML) with nested nodes , ensuring seamless frontend/dashboard consumption .
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Implement solutions integrating LLMs (e.g., GPT models) to extract insights and deliver actionable data.
Cloud & Distributed Systems
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Architect and deploy solutions on cloud platforms such as AWS, Azure, or GCP.
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Build and maintain distributed, scalable systems for AI workloads.
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Optimize models and systems for performance, scalability, and efficiency .
AI Optimization & Prompt Engineering
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Optimize generative AI models for improved accuracy and response quality.
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Develop effective prompt engineering strategies based on understanding how AI interprets data.
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Implement advanced use cases such as:
- Retrieval-Augmented Generation (RAG)
- Conversational systems
- Summarization and translation
Responsible AI & Governance
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Design solutions aligned with Responsible AI principles :
- Fairness
- Transparency
- Security
- Accountability
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Identify, assess, and mitigate risks associated with generative AI systems .
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Ensure compliance with privacy and data protection standards , especially in healthcare environments.
Collaboration & Documentation
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Collaborate closely with cross-functional teams including Product, Data, and Engineering.
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Translate business problems into actionable AI-driven solutions .
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Create clear documentation:
- Technical specifications
- Architecture diagrams
- User guides and presentations
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Contribute to best practices and standards for AI/ML development across the organization.
Required Qualifications
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Proven experience delivering at least one large-scale Generative AI solution .
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Strong hands-on experience with:
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Machine Learning & AI (especially NLP and Generative AI)
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Frameworks: TensorFlow, PyTorch
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Open-source platforms: Hugging Face
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Experience working with:
- LLMs (GPT family, DALL·E, or similar)
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Data pipelines and ML lifecycle management
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Strong software engineering skills for deploying AI into production environments.
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Experience building APIs, system integrations, and scalable architectures .
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Solid understanding of distributed systems design .
Preferred Qualifications
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Experience in healthcare domain or regulated environments.
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Hands-on experience with:
- RAG architectures
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AI-powered dashboards and visualization tools
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Familiarity with CI/CD and DevOps practices .
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Experience designing enterprise-grade, production-ready AI systems .
Technical Skills
- Programming: Python (preferred), SQL
- AI/ML: NLP, LLMs, Generative AI
- Frameworks: TensorFlow, PyTorch
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Tools: Hugging Face, APIs, data pipelines
- Cloud: AWS, Azure, GCP
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Data formats: JSON, HTML, structured outputs
- Version control: Git
Soft Skills
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Strong analytical and problem-solving abilities
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Excellent communica