We are looking for a hands-on Tech Lead to join the Core Platform team within our company ML. Our engineering teams build the foundational systems behind global artifact storage, replication, and distribution – and increasingly power the next generation of AI/ML operations and governance.Our platform is the backbone for ML workloads: managing model binaries, versioning, and scalable runtime environments for ML and AI applications. This role combines deep distributed systems with modern ML infrastructure challenges such as high-throughput inference, safe model rollouts, and multi-cloud GPU efficiency. You will also help evolve core libraries and developer-facing tools, including logging, observability, and visibility components.
As a senior technical leader, you will influence architecture across squads, lead complex development efforts, and remain heavily hands-on.
As a Tech Lead in Core Platform in our company you will
Design and evolve components for managing and distributing ML/AI models and artifacts at scale
Extend the platform to support reliable, high-performance inference and training workflows
Lead cross-team technical initiatives and serve as a reference for distributed systems and ML infra design
Write maintainable, high-quality code in performance-critical areas.
Mentor engineers and drive strong engineering practices
Collaborate with adjacent teams to ensure seamless end-to-end ML platform behavior
Improve the reliability, efficiency, and observability of core services.
As a senior technical leader, you will influence architecture across squads, lead complex development efforts, and remain heavily hands-on.
As a Tech Lead in Core Platform in our company you will
Design and evolve components for managing and distributing ML/AI models and artifacts at scale
Extend the platform to support reliable, high-performance inference and training workflows
Lead cross-team technical initiatives and serve as a reference for distributed systems and ML infra design
Write maintainable, high-quality code in performance-critical areas.
Mentor engineers and drive strong engineering practices
Collaborate with adjacent teams to ensure seamless end-to-end ML platform behavior
Improve the reliability, efficiency, and observability of core services.
Requirements:
7+ years building large-scale backend or distributed systems
Strong foundation in distributed systems (consistency, replication, concurrency, fault tolerance)
Proficiency in Java / Go or similar languages
Hands-on experience with high-performance, scalable, and reliable systems
Ability to lead design discussions and influence technical direction across teams
Curiosity and willingness to work with ML systems and workload patterns
Experience with Kubernetes, container orchestration, or cloud-native infrastructure
Thrive in a collaborative, ownership-driven engineering culture
Bonus Points
Experience with ML model serving, vector DBs, model versioning, or GPU orchestration
Background in secure software supply chain workflows
Strong performance debugging and optimization skills.
7+ years building large-scale backend or distributed systems
Strong foundation in distributed systems (consistency, replication, concurrency, fault tolerance)
Proficiency in Java / Go or similar languages
Hands-on experience with high-performance, scalable, and reliable systems
Ability to lead design discussions and influence technical direction across teams
Curiosity and willingness to work with ML systems and workload patterns
Experience with Kubernetes, container orchestration, or cloud-native infrastructure
Thrive in a collaborative, ownership-driven engineering culture
Bonus Points
Experience with ML model serving, vector DBs, model versioning, or GPU orchestration
Background in secure software supply chain workflows
Strong performance debugging and optimization skills.
This position is open to all candidates.
