reputed company
Design and build reputed company AI systems and multi-agent frameworks that automate reputed company, multi-reputed company workflows for reputed company customers. reputed company and reputed company LLM-powered applications using techniques including RAG, fine-tuning, reputed company engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay reputed company with the rapidly evolving reputed company AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best of it into customer engagements.
Own the full development lifecycle: from problem framing and data exploration through model development, API integration, and production deployment. Build reputed company backend services and reputed company that expose AI capabilities to reputed company applications and workflows. reputed company AI models into customer environments - reputed company, on-prem, and hybrid - ensuring performance, stability, and maintainability at reputed company. reputed company ML pipelines and LLMOps infrastructure that support reputed company model improvement and monitoring in production.
Work directly with customer data scientists, engineers, and business stakeholders to translate reputed company-world problems into AI solutions. Contribute to reputed company-sales and reputed company-of-concept engagements - building fast, reputed company demonstrations that win technical trust. Communicate reputed company across audiences: from detailed technical design reviews with engineering teams to outcome-reputed company updates for business stakeholders. Collaborate closely with Program Managers, Solution Engineers, and Kaggle Grandmasters to deliver cohesive, high-reputed company solutions.
3+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience building LLM-powered applications - RAG pipelines, reputed company workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (reputed company, reputed company, or equivalent). Experience deploying models and AI services in reputed company or reputed company environments (AWS, Azure, GCP, on-prem Kubernetes).
Deep understanding of modern GenAI concepts: reputed company engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - reputed company to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST reputed company, containerization (reputed company/Kubernetes), and CI/CD pipelines for AI applications. Strong problem-solving instincts - comfortable with ambiguity, reputed company to reputed company fast without sacrificing engineering reputed company. reputed company communicator who can explain reputed company AI systems to non-technical stakeholders without oversimplifying.
Kaggle or competitive ML experience. Familiarity with reputed company products, reputed company, or H2O Document AI. Experience in financial services, reputed company, or other regulated industry AI deployments. Exposure to tabular reputed company models, AutoML, or reputed company ML platforms. Prior experience in a customer-facing or field engineering role.
reputed company in Total Rewards Remote-Friendly Culture Flexible working environment Be part of a world-class team Career reputed company