Senior Software Engineer II - MLOps, Retrieval Infrastructure
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POS-23567
About the Role:
HubSpot is at the forefront of empowering businesses with cutting-edge AI, and our MLOps Group is at the heart of this initiative. We are seeking a Senior Software Engineer II with a passion for machine learning operations and data engineering to join our ML Retrieval Infrastructure team.
The ML Retrieval Infrastructure team is part of the MLOps whose goal is to provide infrastructure and tooling to Machine Learning Engineers to be able to excel in their work while also accelerating HubSpot Product & Engineering teams to adopt AI throughout the HubSpot product suite.
Specifically, the ML Retrieval Infra team owns the lower-level components to power retrieval-powered AI applications like RAG (Retrieval Augment Generation) or recommendation use cases. Some of those components include a VectorDB and the layers on top of it.
Responsibilities:
Design & Develop Scalable Retrieval Infrastructure:
Build and maintain the infrastructure powering retrieval-based AI features like Retrieval Augmented Generation and recommendation engines.
Ensure the vector search engine is scalable, reliable, and easy to maintain by enhancing deployment, monitoring, and fault tolerance.
Develop monitoring solutions to maintain the health and performance of the retrieval infrastructure.
Collaborate with AI and Product Engineering Teams:
Partner with machine learning and product engineering teams to integrate retrieval infrastructure into HubSpot’s product ecosystem.
Provide tooling and support to accelerate AI adoption and scaling across products.
Innovate in Retrieval Technologies:
Stay current with advancements in retrieval, databases, and AI infrastructure, applying cutting-edge solutions to enhance HubSpot’s AI capabilities.
Experiment with new retrieval strategies, AI model integration, and distributed systems to improve AI applications.
Ensure Data Security, Privacy, and Compliance:
Implement security and compliance measures, including anonymization and encryption, to manage sensitive data in retrieval systems.
Work with compliance teams to align retrieval infrastructure with HubSpot’s data governance policies.
You'll be a fit if:
You have backend development experience. We work with Java, MySQL, Hbase, AWS, DropWizard, Kafka and Kubernetes primarily, but experience with specific technologies is secondary to understanding programming fundamentals.
Ideally, you have experience managing or working closely with a vector database
Have experience in building scalable retrieval applications desirable
You are excited about current developments and the future of the retrieval space
Have worked with cloud infrastructure
You not only get excited about big, technical challenges but also about being very close to the business and our go-to-market strategies
Take ownership, work collaboratively, and figure things out
Someone who has shown that they can solve complicated technical problems and analyse tradeoffs with empathy for the developers, yet build creative solutions.
About the job
Senior Software Engineer II - MLOps, Retrieval Infrastructure
To see similar active jobs please follow this link: Remote Development jobs
POS-23567
About the Role:
HubSpot is at the forefront of empowering businesses with cutting-edge AI, and our MLOps Group is at the heart of this initiative. We are seeking a Senior Software Engineer II with a passion for machine learning operations and data engineering to join our ML Retrieval Infrastructure team.
The ML Retrieval Infrastructure team is part of the MLOps whose goal is to provide infrastructure and tooling to Machine Learning Engineers to be able to excel in their work while also accelerating HubSpot Product & Engineering teams to adopt AI throughout the HubSpot product suite.
Specifically, the ML Retrieval Infra team owns the lower-level components to power retrieval-powered AI applications like RAG (Retrieval Augment Generation) or recommendation use cases. Some of those components include a VectorDB and the layers on top of it.
Responsibilities:
Design & Develop Scalable Retrieval Infrastructure:
Build and maintain the infrastructure powering retrieval-based AI features like Retrieval Augmented Generation and recommendation engines.
Ensure the vector search engine is scalable, reliable, and easy to maintain by enhancing deployment, monitoring, and fault tolerance.
Develop monitoring solutions to maintain the health and performance of the retrieval infrastructure.
Collaborate with AI and Product Engineering Teams:
Partner with machine learning and product engineering teams to integrate retrieval infrastructure into HubSpot’s product ecosystem.
Provide tooling and support to accelerate AI adoption and scaling across products.
Innovate in Retrieval Technologies:
Stay current with advancements in retrieval, databases, and AI infrastructure, applying cutting-edge solutions to enhance HubSpot’s AI capabilities.
Experiment with new retrieval strategies, AI model integration, and distributed systems to improve AI applications.
Ensure Data Security, Privacy, and Compliance:
Implement security and compliance measures, including anonymization and encryption, to manage sensitive data in retrieval systems.
Work with compliance teams to align retrieval infrastructure with HubSpot’s data governance policies.
You'll be a fit if:
You have backend development experience. We work with Java, MySQL, Hbase, AWS, DropWizard, Kafka and Kubernetes primarily, but experience with specific technologies is secondary to understanding programming fundamentals.
Ideally, you have experience managing or working closely with a vector database
Have experience in building scalable retrieval applications desirable
You are excited about current developments and the future of the retrieval space
Have worked with cloud infrastructure
You not only get excited about big, technical challenges but also about being very close to the business and our go-to-market strategies
Take ownership, work collaboratively, and figure things out
Someone who has shown that they can solve complicated technical problems and analyse tradeoffs with empathy for the developers, yet build creative solutions.