[Remote] Senior Machine Learning Engineer - Platform

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 Senior Machine Learning Engineer will reputed company the architectural reputed company of safety systems, building robust infrastructure for reputed company-time decision-making from sensor data.

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 reputed company the reputed company for principled ship/no-ship reputed company
• Explainability: Partner with Applied Scientists to ensure research outputs are reputed company 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) in a high-growth public company
• A flexible, employee-led remote model
• A professional development stipend
• Comprehensive health and parental leave plans

Company Overview