Senior AI / ML Software Engineer

Company Description Every day, thousands of patients across India face delays, stress, and reduced quality of care due to cumbersome administrative processes and insurance claim challenges. At Vitraya, we directly confront these issues by using advanced AI to streamline healthcare operations, eliminate administrative friction, and ensure healthcare providers can fully focus on patient outcomes.

Role Description

This is a full-time role for a Senior Fullstack AI / ML Engineer. The selected candidate will be responsible for designing, developing, and implementing AI and machine learning models, with a focus on pattern recognition and neural networks. Daily tasks include coding and software development, data analysis, and improving existing algorithms. The Senior Fullstack AI / ML Engineer will work closely with cross-functional teams to ensure the integration of AI solutions into the claims settlement process.

We are looking for a passionate Senior AI / ML Engineer committed to building transformative solutions that positively impact patient care and healthcare delivery.

Responsibilities

Lead the design, development, and deployment of machine learning models for various use cases such as recommendation systems, computer vision, natural language processing (NLP), and predictive analytics.

Work with large datasets to build, train, and optimize models using techniques such as classification, regression, clustering, and neural networks.

Fine-tune pre-trained models and develop custom models based on specific business needs.

Collaborate with data engineers to build scalable data pipelines and ensure the smooth integration of models into production.

Collaborate with frontend / backend engineers to build AI-driven features into products or platforms.

Build proof-of-concept or production-grade AI applications and tools with intuitive UIs or workflows.

Ensure scalability and performance of deployed AI solutions within the full application stack.

Implement model monitoring and maintenance strategies to ensure performance, accuracy, and continuous improvement of deployed models.

Design and implement APIs or services that expose machine learning models to frontend or other systems

Utilize cloud platforms (AWS, GCP, Azure) to deploy, manage, and scale AI / ML solutions.

Stay up-to-date with the latest advancements in AI / ML research, and apply innovative techniques to improve existing systems.

Communicate effectively with stakeholders to understand business requirements and translate them into AI / ML-driven solutions.

Document processes, methodologies, and results for future reference and reproducibility.

Why Join Us :

Direct Patient Impact : Your contributions will significantly enhance patient care quality and reduce administrative burdens on healthcare providers.

Innovation with Real Outcomes : Be part of pioneering AI applications that provide tangible, measurable improvements in healthcare.

Professional Growth : Tackle unique, meaningful challenges that will sharpen your skills and offer growth in a supportive, collaborative environment.

Empowered Team : Enjoy autonomy, flexibility, and the chance to influence core product decisions as part of a dedicated, mission-driven team.

Required Skills & Qualifications

• Experience : 5+ years of experience in AI / ML engineering roles, with a proven track record of successfully delivering machine learning projects.
• AI / ML Expertise : Strong knowledge of machine learning algorithms (supervised, unsupervised, reinforcement learning) and AI techniques, including NLP, computer vision, and recommendation systems.
• Programming Languages : Proficient in Python and relevant ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.
• Data Manipulation : Experience with data manipulation libraries such as Pandas, NumPy, and SQL for managing and processing large datasets.
• Model Development : Expertise in building, training, deploying, and fine-tuning machine learning models in production environments.
• Cloud Platforms : Experience with cloud platforms such as AWS, GCP, or Azure for the deployment and scaling of AI / ML models.
• MLOps : Knowledge of MLOps practices for model versioning, automation, and monitoring.
• Data Preprocessing : Proficient in data cleaning, feature engineering, and preparing datasets for model training.

Nice to Have

Experience with deep learning architectures (CNNs, RNNs, GANs, etc.) and techniques.

Knowledge of deployment strategies for AI models using APIs, Docker, or Kubernetes.

Experience building full-stack applications powered by AI (e.G., chatbots,

recommendation dashboards, AI assistants, etc.).

Experience deploying AI / ML models in real-time environments using API gateways, microservices, or orchestration tools like Docker and Kubernetes.

Solid understanding of statistics and probability.

Experience working in Agile development environments.