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Job Description & How to Apply Below
Nidus Technologies is a fast-growing IT services and consulting firm dedicated to driving digital transformation and innovation. Serving a diverse range of industries, we deliver tailored technological solutions that empower businesses to thrive in an ever-evolving digital world. Our expert team combines strategic planning, advanced technology, and industry-specific knowledge to enable operational excellence. We pride ourselves on delivering meaningful results, ensuring our clients remain future-ready in today’s competitive landscape.
Role Description
This is a full-time hybrid role for an AI/ML Engineer, based in Delhi NCR region. The selected candidate will be responsible for designing and implementing machine learning models, developing algorithms, and conducting data analysis to build AI-driven solutions. Daily responsibilities may include researching new methodologies, optimizing existing systems, applying statistical techniques, and collaborating with cross-functional teams to meet project requirements. The engineer will play a vital role in improving the accuracy and efficiency of our systems and driving innovation within the organization.
The AI/ML Engineer should have 3–7 years of hands on experience building scalable ML and GenAI solutions. Candidates must have strong healthcare domain exposure (claims, clinical data, provider/payor workflows).
Key Responsibilities:
AI/ML Engineering
• Build and deploy production grade ML, NLP, and LLM/GenAI models.
• Implement modern AI architecture patterns: microservices, feature stores, real time/batch inference, embeddings, and retrieval pipelines.
• Convert functional requirements into scalable AI solutions.
Model Development
• Develop and optimize models for claims automation, fraud detection, risk prediction, provider optimization, and document AI.
• Ensure models meet performance, reliability, and scalability standards.
Data & Integration
• Work with data engineering teams to integrate models with healthcare datasets (claims, EHR, clinical notes, PA/UM workflows).
• Ensure PHI/PII safe, compliant pipelines.
MLOps / Platform
• Implement CI/CD for ML/LLM workloads using MLflow, Vertex, Sage Maker, Databricks, Airflow, Argo, and Kubernetes.
• Apply LLM Ops foundations for RAG and GenAI use cases.
Collaboration & Delivery
• Work cross functionally with product, cloud engineering, SMEs, and clinical teams.
• Participate in Agile processes and document reusable patterns and decisions.
Qualifications
3–7 years AI/ML engineering experience.
Strong skills in Python (PyTorch/Tensor Flow), NLP/LLMs/transformers, GenAI tooling, SQL, and data pipelines.
Experience deploying ML/LLM systems in Azure/AWS/GCP.
Solid understanding of U.S. healthcare data and compliant solution design (HIPAA, RBAC, audit logging).
Experience working in ML Ops / LLM Ops environments.
Exposure to large scale AI delivery models
Strong problem solving and ability to break down complex AI tasks.
Clear communication with U.S. stakeholders.
Passion for healthcare transformation through AI.
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