Lead failure analysis and hardware resiliency for Azure cloud infrastructure, driving detection, prediction, and repair of hardware failures across millions of servers.
Compensation
Hardware Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Responsibilities
Lead failure analysis across server components
Define signals, thresholds, diagnostics and repair recipes
Improve isolation accuracy for repairs
Partner with software engineers and data scientists on detection rules
Leverage AI-powered tools and data-driven insights
Serve as a subject matter expert for enterprise technologies, providing advanced technical leadership and leading architecture, design, integration, and implementation of scalable enterprise observability solutions.
Compensation
The expected base salary for this position ranges from $67.17 - 111.94/hour.
Responsibilities
Lead the architecture, design, integration, and implementation of scalable enterprise observability solutions using Dynatrace and IBM SevOne
Implement AIOps capabilities, including Dynatrace Davis AI, causal analysis, anomaly detection, intelligent automation, and AI-driven root cause analysis
Manage observability data, including logs, metrics, events, and alerts, ensuring effective telemetry governance, alert optimization, and cost control
Partner with business stakeholders, technology teams, and vendors to gather requirements and deliver complex technical solutions
Establish technology standards, architecture guidelines, and industry best practices
Requirements
Bachelor's degree in Computer Science, Computer Engineering, or a related field
Lead engineering strategy and modernization of enterprise storage platforms across JPMorgan Chase.
Compensation
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity.
Responsibilities
Lead engineering strategy, modernization, and delivery of enterprise physical storage platforms
Lead engineering capabilities across block and file storage, storage networking, replication, capacity and performance management, data protection, resiliency, and recovery
Establish engineering standards for storage provisioning, configuration, lifecycle management, observability, performance, availability, and infrastructure automation
Set and scale multi‑department strategy for AI‑enabled engineering and automation
Requirements
Bachelor's degree in Computer Science or related field
Nice to have: Experience with storage area networks
Own the AI systems at the heart of the product, building end‑to‑end ML pipelines and cloud architecture for predictive maintenance of commercial fleets.
Compensation
Early-stage compensation: 130 ~ 150k salary, ~1.5% experience and location - we're happy to talk through the details early in the process.
Responsibilities
Build data pipelines that move sensor data from vessel edge devices to cloud over satellite links
Stand up cloud architecture on AWS for real‑time and batch processing
Integrate historical maintenance records from CMMS databases
Develop ML models for anomaly detection and failure prediction using isolation forests, autoencoders, gradient‑boosted trees, and LSTMs
Design fleet‑wide and vessel‑specific modeling approaches
Seeking a highly skilled Vision System Data Science Engineer (Level 4) to much the design, development, and deployment of advanced computer vision and machine learning solutions for complex industrial and manufacturing applications.
Responsibilities
Design, develop, and deploy computer vision algorithms for detection, classification, segmentation, anomaly detection, and predictive analytics.
Build scalable machine learning and deep learning models using image, video, and multimodal sensor data.
Lead the complete data science lifecycle, including data collection, labeling, feature engineering, model training, validation, deployment, and monitoring.
Develop robust image-processing pipelines utilizing modern computer vision frameworks and cloud technologies.
Define data quality standards and establish model performance metrics to ensure production readiness.
Lead the product strategy, vision, and roadmap for Threat Detection and Prevention within Box Shield and the broader Box Security ecosystem.
Compensation
$217,000—$271,500 USD
Responsibilities
Define and execute the product strategy, vision, and roadmap for Threat Detection and Prevention within Box Shield and the broader Box Security ecosystem.
Lead the development of machine learning-driven anomaly detection models and automated containment workflows to combat threats such as ransomware, credential compromise, account takeover (ATO), and insider risks.
Spearhead the integration of Box AI and generative threat analysis, empowering security analysts and admins with plain-language alert summaries, threat context, and recommended remediation actions.
Partner deeply with Engineering, Data Science, Security Architecture, and UX Design experts to deliver enterprise-grade security capabilities at cloud scale.
Drive key business and operational metrics for Box Shield, such as detection accuracy, time-to-containment, feature adoption, and enabled revenue growth.
Develop and launch on-device machine learning technologies to keep users safe from fraud while maintaining privacy, designing models that work within resource constraints like model size and inference budgets.
Locations (2)
Austin, Texas, United States
New York City, New York, United States
Responsibilities
Develop and launch on-device technologies that keep users safe
Work closely with engineering, security, program management, and business partners
Build models that run in real time and in the background on the device
Lead end-to-end security assurance effort for Windows, including compliance, risk assessment, vulnerability research and tooling.
Compensation
Security Assurance M6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.
Responsibilities
Partner with engineering and product teams to ensure security requirements are met at scale
Execute and evolve the security assurance process for Windows teams
Lead cross-team security initiatives and coordination
Influence without authority by building solid partnerships
Deliver end-to-end execution on high-impact security efforts
Requirements
Master's Degree in Statistics, Mathematics, Computer Science, Risk Management, Cyber Security, or related field
Bachelor's Degree in Statistics, Mathematics, Computer Science, Risk Management, Cyber Security, or related field
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