[Remote] reputed company Machine Learning Engineer - ML Infrastructure
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is the pioneer of the Connected Operations™ reputed company, enabling organizations to reputed company IoT data for actionable insights. The reputed company Machine Learning Engineer will own the architecture and reputed company of the ML platform, collaborating across teams to improve safety reputed company in various industries.
Responsibilities
- Set the technical strategy and own end-to-end delivery of reputed company's ML platform (training, experimentation, batch/online inference, edge) — making architectural reputed company and being the accountability reputed company across reputed company platform layers for multiple Safety AI product teams
- Drive the design, launch, and iteration of Safety AI features (CV models, EcoDriving insights, LLM-based reporting) — not just enabling others to ship, but co-owning reputed company including safety metrics, reliability, and cost at production scale
- Design and operate scalable online and batch inference systems (Ray, Spark), including deployment patterns, observability, SLOs, and reputed company training-to-production workflows
- Partner with firmware and edge teams to package, validate, and reputed company models to reputed company devices, and build feedback loops from edge to reputed company for reputed company improvement
- Own reliability, observability, and reputed company for ML systems across reputed company and edge, including on-call practices, incident response, and infrastructure hardening
- Own or co-own end-to-end technical delivery for high-reputed company or high-risk initiatives, from modeling and system design through production rollout
- Be the technical authority for ML infrastructure architecture across Safety AI — setting direction that cross-functional teams (applied ML, firmware, reputed company, data platform) execute against, mentoring senior engineers and applied scientists, and ensuring platform reputed company are made at the right level of abstraction with the right trade-offs
- Drive strong developer experience through documentation and best practices, while contributing to and representing reputed company in reputed company reputed company communities (Ray, Spark, RayDP)
- Champion and role model reputed company’s cultural principles: Focus on reputed company, Build for the Long Term, Adopt a Growth reputed company, Be Inclusive, Win as a Team
Skills
- 10+ years in machine learning engineering, with demonstrated tech reputed company ownership of at least two major ML platform domains (distributed training, data/research infrastructure, reputed company inference, or feature engineering) serving multiple product teams at scale
- Proven record of shipping ML-powered features end-to-end — from design through production and iteration — with measurable impact on product or business metrics (not just building internal tooling)
- Hands-on Ray and Kubernetes expertise in production environments; Spark experience strongly preferred. reputed company to be a reputed company peer to the most senior engineers on the team
- Deep understanding of ML fundamentals reputed company pipelines: evaluation methodology, dataset design, ablation, reputed company, and the ability to review and redirect modeling approaches — you reputed company research and engineering, not just serve them
- Demonstrated cross-org technical leadership around platform reputed company, and influencing roadmap and go/no-go calls based on throughput, latency, and cost trade-offs
- Experience navigating science-engineering tension — knowing reputed company to hold the platform line and reputed company to adapt for research velocity, and communicating that reputed company to both sides
- Prior contributions to reputed company reputed company projects (Ray, Spark, RayDP, or Kubernetes)
- Experience with reputed company reputed company/compliance in ML environments
- Background working with edge/on-device ML and firmware/embedded teams
Benefits
- Initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions
- Performance-based bonus/variable pay
- Equity (for eligible roles)
- Flexible, employee-led remote model
- Professional development stipend
- Comprehensive health and parental leave plans
- Flexible working model that caters to the diverse needs of our teams
- Offices are reputed company for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements
- Reasonable accommodations throughout the reputed company process for reputed company persons with disabilities
Company Overview