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Senior Staff ML Ops Engineer
Job Location:
Job Location:
Dallas, TX - USA
Yearly Salary:
USD 184000 - 272000
Yearly Salary:
Posted:
26 September 2026 (7 hours ago)
Posted:
Application Deadline:
24 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Waabi founded by AI visionary Raquel Urtasun is the leader in Physical AI. With a world-class team were unlocking the next era of autonomous transportation with technology thats powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI automotive logistics and deep tech.
With offices in Toronto San Francisco Dallas and Pittsburgh Waabi is growing quickly and looking for diverse innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit:
You will..
- Build and evolve our training infrastructure on Kubernetes with Infrastructure GPU scheduling autoscaling multi-node distributed jobs capacity strategy and the operators and workflow engines that keep long-running training reliable.
- Shape the developer-facing surface CLIs SDKs job submission templates paved paths designed with the teams wholl use them. Make the common case one command and keep the uncommon case possible.
- Shorten the inner loop. Time to first training run edit-to-signal latency local iteration before a job hits the cluster fast failure over slow mystery. Measure it publish it drive it down.
- Evangelize best-in-class tooling and frameworks. Track what the ecosystem is shipping evaluate honestly and make the case with working prototypes and migration paths or say plainly when a shiny thing isnt worth the switching cost.
- Strengthen the data and artifact layer. Dataset versioning sharding and high-throughput loading of large multimodal sensor data so jobs saturate GPUs instead of waiting on I/O.
- Turn one-off Python into durable tooling tested documented observable libraries CLIs and services with sane defaults and deletions where theyre overdue.
- Make experiments legible with the teams who live in them: experiment hygiene dashboards researchers trust a real model registry and lineage from dataset to checkpoint to simulation result.
- Ship CI/CD for models alongside autonomy and simulation so a model change is validated the same way a code change is.
- Build observability across the ML stack utilization throughput failure modes queue times cost per experiment. When a job fails at 3am on node 47 the researcher should find out why without you.
- Treat docs onboarding and support as product surface golden-path guides a new researcher productive on day twooffice hours that turn repeat questions into shipped fixes.
- Drive adoption not just availability. Prototype with real users watch them work iterate. A tool nobody adopts didnt ship.
- Make the platform boringly reliable fewer failures faster recovery and none of the manual steps that quietly cost a team days.
- Build guardrails that dont feel like walls with Security IT and Infrastructure: access controls data handling and cost governance that hold up in an IP-sensitive environment while staying self-serve.
Qualifications:
- 5 years of software or infrastructure engineering including tools or platforms used by other engineers and operating ML or data-intensive production systems.
- Hands-on Kubernetes expertise GPU scheduling autoscaling Helm or equivalent networking fundamentals and the ability to debug a cluster under load rather than restart it.
- Excellent Python and a track record of designing APIs and CLIs other people enjoy using.
Practical AWS depth: object storage at scale IAM GPU compute networking cost management and infrastructure as code (Terraform Pulumi or similar). - Distributed training in PyTorch (DDP FSDP or similar) plus experiment tracking and model registry tooling from the perspective of someone who made them pleasant for others to use.
- Fluency with containers CI/CD and modern build systems including large monorepos.
- The ability to influence without authority: evaluate a framework on its merits pilot it credibly and persuade skeptical senior engineers to change how they work.
- A collaborative default youd rather co-own a system than draw a boundary around your part of it.
- User empathy: youd rather fix the third-most-interesting problem blocking ten people than the most interesting one blocking nobody.
- Strong product instincts strong writing and comfort operating autonomously in ambiguous territory.
- Passionate about self-driving technologies and frontier AI and about what a small world-class team can do with the right infrastructure.
Bonus/nice to have:
- Internal developer platform research platform or DevEx work with a story about a tool whose adoption you grew from zero.
- Large-scale distributed GPU training: hundreds to thousands of accelerators NCCL high-performance cluster networking collective communication tuning.
- High-throughput loading of LiDAR or camera data and formats such as Parquet or WebDataset.
- Workflow and scheduling systems Argo Workflows Ray Flyte Kubeflow or Slurm.
- Build-system depth (Bazel or similar) including remote caching in a monorepo.
- Simulation infrastructure or large-scale batch evaluation pipelines.
- Background in ML robotics or autonomous systems infrastructure.
- Security- and IP-sensitive production environments.
- Open-source contributions to ML infrastructure or developer tools.
The US yearly salary range for this role is: $184000 - $272000 USD in addition to competitive perks & benefits. Waabi (US) Inc.s yearly salary ranges are determined based on several factors in accordance with the Companys compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role including equity incentive awards and an annual performance bonus.
Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site off-site & virtually.
- As we grow this list continues to evolve!
Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!
Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive inclusive and accessible workplace for all our employees. We seek applicants of all backgrounds and identities across race color ethnicity national origin or ancestry age citizenship religion sex sexual orientation gender identity or expression military or veteran status marital status pregnancy or parental status caregiver status disability or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
Required Experience:
Staff IC
About Company
The US yearly salary range for this role is: $184,000 - $272,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective ... View more
