Senior AI Engineer, Services Special Projects

What you'll do

• Build and optimize LLM-based applications using techniques like quantization, distillation, and compilation for production environments.
• Develop scalable ML infrastructure, including CI/CD pipelines, Kubernetes deployments, and high-traffic RESTful or GraphQL APIs.
• Manage the full model lifecycle from initial experimentation and fine-tuning to deployment, monitoring, and retirement.
• Design and implement robust data pipelines for multimodal data ingestion using feature stores and lineage-tracked storage.
• Establish model governance frameworks including audit trails, approval gates, and compliance controls.
• Implement safety guardrails and privacy-preserving techniques to protect user data and ensure safe model outputs.
• Develop observability tools to monitor performance metrics such as latency, throughput, and cost efficiency.
• Mentor junior engineers and establish technical standards for MLOps practices across the organization.

What we're looking for

• Master's degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in Machine learning and software engineering.
• Proven track record of shipping production-grade ML/LLM systems.
• Strong understanding of LLMs, fine-tuning, prompt engineering, and RAG patterns.
• Experience building pipelines for multimodal data and integrating LLM inference with vector search technologies.
• Hands-on experience deploying and optimizing LLMs using frameworks like Triton, vLLM, or SGLang on Kubernetes.
• Proficiency in Python and working proficiency in Java or Scala.
• Experience with MLOps tools including CI/CD pipelines, Airflow, and model versioning systems like MLflow or DVC.