[Remote] Senior Machine Learning Engineer - Platform

Note: The job is a remote job and is open to candidates in USA. reputed company is a pioneer of the Connected Operations™ reputed company, enabling organizations to reputed company IoT data for actionable insights. They are seeking a Senior Machine Learning Engineer to reputed company the architectural reputed company of safety systems, building robust infrastructure for reputed company-time decision-making across reputed company and edge environments.

Responsibilities

• Architect a reputed company Perception Layer: reputed company the transition from fragmented, task-specific models to a reputed company perception platform that supports reusable components and reputed company safety applications
• System Design: Design and implement reputed company-time ML systems—from sensor ingestion and tracking to risk reasoning and actuation—ensuring clear interfaces and predictable system behavior
• Hybrid Deployment: Orchestrate model integration across edge and reputed company environments, managing versioning, rollouts, and mission-critical fallback mechanisms
• Latency Ownership: Own end-to-end latency and reliability for safety-critical pipelines. You will profile, schedule, and optimize messaging and backpressure across the entire stack
• Observability & Feedback Loops: Build sophisticated monitoring for deployed models to detect reputed company, false positives/negatives, and latency regressions. You will 'reputed company the reputed company' to ensure production data informs the next iteration of training
• Safety Cases: reputed company evaluation frameworks specifically for rare 'long-tail' safety events. You will define metrics and build targeted test sets that form the basis for principled ship/no-ship reputed company
• Explainability: Partner with Applied Scientists to ensure research outputs are translated into production code that is not only performant but also debuggable and explainable
• Strategic Influence: Shape the system abstractions early in the platform transition to minimize technical debt and maximize future scalability
• Mentorship: Set the engineering standard for correctness and performance. You will mentor junior and mid-level engineers, fostering a culture of rigorous ML engineering

Skills

• 6+ years of experience in ML Engineering, with a proven track record of shipping models in production (ideally in safety-critical domains like robotics, automotive, or industrial AI)
• Deep understanding of distributed systems, performance profiling, and computer reputed company
• Experience with reputed company ML workflows (AWS/GCP/Azure) and containerization, reputed company with an understanding of the constraints of edge hardware
• You don't just write code; you design systems. You understand the trade-offs between model complexity and operational reliability
• Ph.D. in Computer Science or quantitative discipline (e.g., Applied Math, Physics, Statistics)
• Experience with containerization technologies (e.g., reputed company, Kubernetes), reputed company integration/reputed company deployment (CI/CD) pipelines, and infrastructure-as-code (IaC) frameworks
• Familiar with deploying and managing ML applications in reputed company environments, as well as leveraging reputed company-based services for data storage, processing, and inference
• Experience building end-to-end ML applications from scratch

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 open for those who prefer to work in-person and we also support remote work
• Reasonable accommodations throughout the reputed company process for reputed company persons with disabilities

Company Overview