Engineering Manager, ML Training Infrastructure
Key Skills for This Role
Full Job Posting
RESPONSIBILITIES
- Lead engineers and foster a collaborative and innovative environment.
- Manage and nurture a group of around 7–8 engineers, offering technical vision, mentorship, professional growth, and effective project delivery.
- Establish and articulate the technical vision and future roadmap for machine learning training infrastructure.
- Direct the architecture, construction, and operation of resilient systems supporting massive ML model training workloads.
- Construct and maintain Kubernetes-driven compute clusters and container ecosystems tailored for machine learning workloads.
- Oversee and optimize GPU fleets, addressing cluster scheduling, resource utilization, system stability, and cost performance.
- Advance distributed model training capabilities and workload management leveraging frameworks like Ray and adjacent tools.
- Enhance workflow orchestration platforms by deploying and supporting solutions such as Airflow, Temporal, and similar pipeline frameworks.
- Elevate the system resilience, monitoring insights, elasticity, and operational productivity of our ML training stack.
- Work closely alongside AD/ADAS, Woven City, and internal platform partners to gather feature requests and ship infrastructure solutions that accelerate development.
- Partner with cross-functional engineering groups to specify platform interfaces, APIs, system architectures, and operational standards.
- Translate high-level organizational objectives and user requirements into concrete, executable engineering milestones with product leads.
- Institute rigorous software practices across implementation, code reviews, automated testing, continuous deployment, and live site management.
- Engage in production support workflows, lead post-incident reviews, and champion system refinements based on operational findings.
- Balance immediate client feature requests against long-term architectural stability, technical hygiene, and system maintainability.
- Foster an inclusive, highly collaborative, and excellence-driven engineering culture throughout Woven by Toyota.
MINIMUM QUALIFICATIONS
8+ years of experience in software engineering, with at least 2 years in a leadership role.
Proven track record mentoring and managing high-performing software or platform teams.
Demonstrated expertise in architecting, deploying, and maintaining large-scale mission-critical infrastructure.
Deep technical mastery of Kubernetes orchestration alongside containerized runtime systems.
Hands-on exposure to cloud platform architectures and highly resilient distributed systems.
Background engineering platform foundation layers designed for machine learning model development or data pipeline intensive workloads.
Practical understanding of massive GPU cluster management, hardware scheduling algorithms, and capacity efficiency tuning.
Operational background overseeing high-availability environments, leading post-incident reviews, and advancing monitoring capabilities.
Excellent interpersonal abilities to align technical roadmaps across diverse engineering partners and leadership stakeholders.
NICE TO HAVES
Experience working with Japanese customers or clients.
Experience with Golang development (especially for cloud services)
Experience in the automotive industry or knowledge of automotive software development (e.g., ASPICE, V-model).
Experience working in environments with a focus on security and safety.
English/Japanese bilingual ability
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