Position: MLOps Engineer

Location: Remote (U.S. preferred, with hubs in SF, NYC, Chicago, and Austin) 

Cercle Overview & MIssion
Cercle™ is an AI technology company focused on advancing healthcare for all women. Our AI platform and tools work together to unlock insights for women's healthcare companies. Current and future customers range from clinics and labs to hospitals and pharmaceuticals. Engineers at Cercle are working at the forefront of AI, ML, data engineering, and women’s healthcare. As an MLOps Engineer, you’ll build cutting-edge AI accessible to healthcare professionals.

Key Responsibilities:
Graph Embeddings & Vector Databases
● Build and maintain pipelines for generating real-time embeddings from heterogeneous graphs.
● Optimize embedding generation and retrieval using vector databases (e.g., Pinecone, Weaviate, Milvus, FAISS, Vespa)
● Ensure low-latency, high-throughput performance for real-time inference.

AI Agent Deployment
● Architect, deploy, and scale AI agent–driven products in production environments.
● Implement supporting infrastructure for task orchestration, memory, context management, and multi-agent collaboration.
● Integrate agents with enterprise systems, APIs, and external data sources securely.

ML Ops & Infrastructure
● Develop and maintain CI/CD pipelines for ML models, embeddings, and AI agent systems.
● Deploy on cloud-native environments (AWS, GCP, Azure, or hybrid) using Kubernetes, Docker, and microservices architecture.
● Automate monitoring, logging, and alerting for ML workflows and AI agents at scale.
● Implement observability frameworks for embeddings, vector search quality, and agent performance.

Tech Stack proficiency requirements:
● Proven experience in ML Ops, AI Infrastructure, or Applied ML Engineering roles.
● Strong knowledge of graph ML, embeddings, and heterogeneous data structures.
● Hands-on experience with vector databases and real-time retrieval systems.
● Experience deploying AI agent–based products or multi-agent frameworks.
● Proficiency in Python, ML frameworks (PyTorch, TensorFlow), and deployment stacks (Kubernetes, Docker).
● Strong understanding of cloud infrastructure (AWS, GCP, or Azure).
● Experience with monitoring, observability, and scaling AI workloads.

Bonus Points:
● Experience with LangChain, LlamaIndex, RAG pipelines, or agent frameworks.
● Familiarity with distributed systems, streaming data (Kafka, Flink, Spark Streaming).
● Knowledge of security and compliance practices for enterprise AI deployments.
● Contributions to open-source ML Ops, vector databases, or agent framework

Benefits:
● Competitive base salary + meaningful stock options
● Highly flexible remote work with a global team, and annual company retreats
● Medical, dental, vision, and 401k plans
● Unlimited PTO in addition to U.S. federal holidays off
● The chance to shape cutting-edge AI products from the ground up

If interested, please send your resume to recruiting@cercle.ai
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