Member of Technical Staff, ML Workload Platform

Cohere

. Own the platform that schedules and runs training, evaluation, and reinforcement-learning jobs on Kubernetes .

Posted 11/6/2026full-timeRemote • Canada, United StatesLead💰 CA$300,000 - CA$420,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in managing job platforms and Kubernetes environments, with a strong focus on automation, scalability, and observability in machine learning workflows. Proven ability to collaborate with diverse teams and troubleshoot complex production issues effectively.

Highest-signal resume keywords

Kubernetes ManagementMachine Learning WorkflowsPython ProgrammingDistributed Systems JudgmentOn-Call Support

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Job Platform ManagementBatch System ExperienceScheduling and QueuesMulti-Tenant FairnessContainer Networking (CNI)Checkpoint StorageGPU-Cluster ExperienceAutomation and Infrastructure-as-CodeTroubleshooting Production FailuresPerformance Problem Resolution

Soft Skills

Collaboration with ResearchersProblem-Solving in Fast-Moving Environments

Tools & Technologies

JAXPyTorchTensorFlowHigh-Performance Computing Environments

Industry Keywords

Reinforcement LearningCapacity AllocationJob FailuresRuntime IsolationObservability

Tech Stack

Tools & technologies

Distributed SystemsKubernetesPythonPyTorchTensorflowGo

About the role

Key responsibilities & impact

Own the platform that schedules and runs training, evaluation, and reinforcement-learning jobs on Kubernetes
Manage capacity allocation, job failures, and platform-cause visibility for researchers
Build networking and runtime isolation, including agent and sandbox environments
Collaborate with the data infrastructure team on checkpoint and training-artifact storage
Troubleshoot production failures and performance problems
Build automation, infrastructure-as-code, and observability for maintainability
Work with AI researchers and ML engineers on stability, scalability, and observability
Participate in a compensated 24x7 on-call rotation

Requirements

What you’ll need

Experience running a job platform, batch system, or Kubernetes controllers in production
Experience with scheduling, queues, and multi-tenant fairness
Distributed systems judgment, including retries, partial failure, and knowing what not to automate
Experience with ML training workflows, RL sandboxes, container networking (CNI), or checkpoint storage at scale
Direct GPU-cluster experience is a plus
Programming experience in Python or Go
Experience working with researchers, ML engineers, or teams with differing goals
Experience finding bottlenecks, proposing fixes, and driving implementation in a fast-moving environment
Availability for a compensated 24x7 on-call rotation
Authorization to work in the country of residence
Required to answer questions about Kubernetes at scale and ML/HPC infrastructure, including GPU/TPU clusters, JAX, PyTorch, TensorFlow, and high-performance computing environments

Benefits

Comp & perks

Weekly lunch stipend of $75/£75 or equivalent in local currency
Full health and dental benefits
Separate mental health budget
RRSP matching
401K
Pension Scheme
100% parental leave top-up for up to 6 months, for either parent
Annual enrichment benefits for arts and culture, fitness/wellness, quality time, and workspace improvement
Education and learning stipend for conferences, courses, and coaching
6 weeks of paid vacation (30 working days)
Budget for traveling to other offices if remote
Annual company offsite
Daily lunch program, snacks, and regular community and social events for office-based employees
Co-working benefit for employees not near an office
$500 home office stipend
Compensated 24x7 on-call rotation