Role overview
We are looking for a highly skilled and visionary Senior Machine Learning Engineer to lead the design, development, and deployment of advanced AI solutions across our platform. This role involves building LLM-powered systems, intelligent agents, and traditional ML/DL models that drive innovation in mental health care technology. You will mentor junior engineers, influence architectural decisions, and ensure scalability and performance of AI-driven products. Your expertise will help shape the next generation of multimodal AI applications that deliver measurable business impact.
Lead AI System Design: Architect and implement scalable, production-grade AI systems using Python and modern ML frameworks.
LLM & Agentic Systems: Design and optimize LLM-powered workflows and autonomous AI agents using orchestration frameworks (LangChain, LlamaIndex, CrewAI, Semantic Kernel).
Advanced Model Development: Build, fine-tune, and deploy deep learning models (PyTorch, TensorFlow, Keras) for NLP, vision, and multimodal tasks.
Data Engineering & Analytics: Oversee data pipelines, perform advanced analytics, and create actionable insights through visualization.
Database Expertise: Design and optimize data storage and retrieval using SQL and PostgreSQL for large-scale AI workflows.
Integration & Deployment: Drive seamless integration of AI models with APIs, microservices, and cloud infrastructure.
Mentorship & Leadership: Guide junior engineers, review code, and enforce best practices in ML engineering and MLOps.
Innovation & Research: Stay ahead of emerging trends in Generative AI, agent architectures, and open-source AI ecosystems.
What we're looking for
Expertise in model quantization, distillation, and optimization for large-scale deployment.
Experience with microservices, Kubernetes, and GitOps practices.
Contributions to open-source AI/ML projects or published research.
Familiarity with vector databases (Pinecone, Weaviate, ChromaDB).