AI/ML engineer

Department/Project Description

Client is a leading medtech company building AI-enabled products; as an AI Engineer you will design, develop, and deploy advanced AI applications focused on LLMs, API-driven architectures, and AI-powered local apps, collaborating with cross-functional teams to deliver scalable, secure, high-performing solutions that enhance user experience and operational efficiency.



Job Description

• Bachelor’s/Master’s in Computer Science, AI/ML, or related field
• 2+ years of experience in AI/ML engineering with hands-on work in LLMs and generative AI
• Strong Python skills; experience with LangChain, Hugging Face Transformers, and/or OpenAI API
• Proven experience designing and building APIs (REST/GraphQL, FastAPI) and microservices
• Experience building RAG pipelines and working with vector databases
• Hands-on with cloud platforms (Azure/AWS/GCP) and containerization (Docker, Kubernetes)
• Ability to design, fine-tune, and evaluate LLMs; strong prompt engineering practices
• Familiarity with AI deployment/inference pipelines (on-prem and cloud)
• Understanding of data privacy, security, and compliance in AI systems
• Clear, concise communication and documentation skills; ability to collaborate across functions
• English: fluent (B2+) spoken and written

Job Responsibilities

• Design, develop, and deploy AI applications leveraging LLMs for real-world use cases
• Build retrieval-augmented generation (RAG) solutions integrating external knowledge bases
• Design and implement secure, scalable APIs for AI services and platform integration
• Fine-tune LLMs for domain-specific tasks; define prompts, evaluation, and guardrails
• Implement AI inference pipelines across on-prem and cloud environments (Azure/AWS/GCP)
• Integrate AI features into local and enterprise applications in partnership with product/engineering
• Monitor and optimize model accuracy, latency, reliability, and cost in production
• Document approaches, experiments, and decisions; communicate findings to technical/non-technical stakeholders
• Track emerging AI technologies and recommend best practices for adoption