Senior Machine Learning Engineer

Join our team as a Senior Machine Learning Engineer, where you will architect high-scale distributed systems and lead the development of autonomous agents. You will work with asynchronous systems, large-scale data processing, and design sophisticated AI agents. Additionally, you will be responsible for the architectural design of containerized services on Kubernetes. Enjoy a range of benefits including health and dependent savings accounts, paid parental leave, retirement savings, and equity opportunities.

• Architect high-scale distributed systems that process massive data volumes to fuel the Agentic AI ecosystem.
• Lead the development of autonomous agents that drive complex automation and insights for enterprise customers.
• Design and optimize high-throughput, event-driven systems using Apache Kafka and build large-scale data pipelines using Apache Spark or Flink.
• Hands on experience with agentic frameworks (e.g., AutoGen, CrewAI, or custom orchestration layers), RAG, MCP, fine tuning models and prompt engineering
• Expertise in distributed systems, asynchronous architectures (Kafka), and large-scale data processing (Spark/Flink)
• Agentic observability using Langfuse, Evals frameworks for Testing/Resilience
• 5–8 years of experience in backend engineering using Java, Python, or Go
• Advanced IaC: Expertise in building reusable Terraform modules and managing complex multi-region cloud deployments
• Vector DB Optimization: Deep experience in indexing strategies (HNSW vs IVF) and performance tuning for high-concurrency vector databases at scale
• AI Ops: Experience with LLM deployment optimization (e.g., vLLM, TensorRT-LLM) or managing proprietary model inference endpoints