All careers Open role / Full-time
Full-timeSenior Kozhikode · Hybrid
Senior Machine Learning EngineerArchitect, build, and deploy production-grade ML pipelines, LLM fine-tuning, and RAG architectures for healthcare and visual intelligence systems.
Apply for this role 01Intermediate capability 02Real product work 03Hybrid collaboration Role standard
Ready to contribute. Still ready to learn.
Typically 4+ years of hands-on experience designing, training, and deploying AI models in production.
What matters most
Show us how you think, what you have built or learned, and how you improve work after feedback.
Responsibilities
What you will own.
• 01Design and implement reliable pipelines for model training, evaluation, and deployment.
• 02Build robust retrieval-augmented generation (RAG) frameworks with clean indexing and validation.
• 03Optimize model performance, memory footprint, and API latency for high-throughput client systems.
• 04Collaborate with product and data engineering teams to transition ideas into scalable microservices.
• 05Establish best practices in data versioning,



experiment tracking, and model monitoring.

Intermediate skills
What you should bring.
• Strong Python proficiency and deep understanding of PyTorch or TensorFlow
• Experience with LLM orchestration frameworks (LangChain, LlamaIndex) and API integrations
• Hands-on vector search engineering (pgvector, Qdrant, Pinecone)
• Applied MLOps fundamentals: Docker, container orchestration, MLflow, and cloud deployments
• Deep understanding of statistical testing, evaluation metrics, and error analysis

Helpful, not required: Experience in healthcare data standards, Edge AI, tensor optimization (TensorRT), or custom fine-tuning of open-weight models is a strong plus.
Early outcomes
What good progress looks like.
01A scalable, production-ready pipeline for generative or computer vision workflows
02Measurable improvement in model inference latency, retrieval accuracy, or precision metrics
03Documented eva

📌 Senior Machine Learning Engineer (Bengaluru)
🏢 Xynvia
📍 Bengaluru