Top Remote Systems Engineer Jobs

The role involves designing and maintaining core systems for reliability and automation while improving developer workflows and operational visibility. It requires proficiency in Rust, systems engineering, and experience with databases and distributed systems.

Lead a team in the engineering design and execution of SCADA, network, and controls systems for solar projects, ensuring quality and project milestones are met while mentoring junior engineers.

The role involves architecting molecular machine learning systems, building workflows for data generation and training, and collaborating between research scientists and infrastructure teams.

The Senior Systems Engineer will provide expertise in systems engineering for complex systems development, mentor team members, improve processes, and lead modeling efforts using MBSE methods.

Support advanced cyber environments and enterprise infrastructure within a DoD setting by designing, configuring, and maintaining network and system architectures, VMs, and security protocols.

The Senior Systems Engineer manages systems engineering support for tactical communications, leading design, integration, testing, and stakeholder requirements interpretation.

Design, build, and operate full‑stack and backend services to support Sales, Marketing, and Finance. Lead technical design and production deployment of GenAI/ML features, own SDLC, ensure observability and validation, partner with cross-functional teams, and mentor engineers to deliver business outcomes.

Design and implement Ubuntu integration for IoT and server-class hardware, working with partners on performance enhancements and testing strategies.

Lead design, implementation, testing, and support of distributed control and digital safety systems for nuclear power projects. Manage engineering teams, oversee design reviews, create/approve engineering and test documentation, integrate hardware/software, troubleshoot systems, engage with customers, and support proposals and vendor selection.

Lead large technical teams for defense systems engineering: translate requirements into low-risk solutions, produce technical documentation, guide cross-functional teams, report technical status, evaluate performance, and recommend training to advance technical capabilities.

Lead systems engineering for new LEO satellite development and post-launch operations. Validate vendor designs, perform antenna pattern and digital beamforming analyses, assess payload impacts on power/thermal and system capacity, and support cross-functional vendor integration and operations.

The Principal Systems Engineer will manage Kafka clusters, ensuring performance and security while collaborating with development teams on integrations. Responsibilities include monitoring, troubleshooting, and maintaining documentation for Kafka solutions, as well as developing disaster recovery plans.

As a Systems Safety Engineer, you'll develop safety methodologies, assess safety for unmanned aircraft, and ensure compliance with federal safety regulations, collaborating across teams to enhance aviation safety technologies.

Develop software for communication systems in aviation, focusing on link management, systems integration, and network security across embedded and application layers.

As a Sr. Systems Engineer, you will lead system development for safety-critical flight systems, managing requirements, design, and certification challenges.

Own and operate end-to-end billing across consumer and B2B: seats, usage, cost centers, bundling, international pricing and payments. Reconcile state across RevenueCat, Stripe, Sequence, enable rapid SKU/pricing rollout, build robust testing, and expand enterprise billing features and global payment coverage.

The Senior Systems Engineer will ensure system availability, security, and performance for a large-scale global infrastructure at Automattic, addressing system health and facilitating developer efficiency.

Develop backend systems for 3D AutoReview, including geometry parsing, model analysis, quality detection, rule systems, scalable APIs, and AI-assisted review workflows. Collaborate with backend, frontend, product, and machine learning teams to deliver production features. Build extensible systems for custom 3D rules and reference data while experimenting with CAD, machine learning, and large language model technologies.

Develop and implement customer information solutions while serving as a liaison between stakeholders and Decision Resources. Responsibilities include requirements gathering, systems analysis, development, QA testing, UAT support, user training, SDLC execution, and post-production support. The role also provides production support for Syteline products, including EDI, ecommerce, OCR transactions, supply chain and warehouse management, and general user issues.

Plan, forecast, and optimize hardware capacity for storage, compute, and network. Build predictive models and automated forecasting pipelines, monitor cluster performance, align cross-functionally with engineering, operations, and finance, and support procurement and deployment decisions to ensure scalable, cost-efficient platform reliability.

Design and optimize high-performance kernels and custom operators for attention, MoE, GEMM, quantization and collective communication across NVIDIA, AMD and AWS Trainium. Improve LLM inference runtimes, develop distributed training/inference solutions at scale, use compilers and SDKs (Neuron, Torch Dynamo, PyTorch/XLA), contribute to open-source, and publish technical findings.

Leads integration, commissioning, startup, troubleshooting, and optimization of ultra-pure water, wastewater, reuse, and utility systems for semiconductor facilities. Develops standards, documentation, layouts, and execution methods; supports system turnover, testing, operational readiness, and ramp activities. Collaborates with engineering, operations, construction, suppliers, customers, and end users while providing technical education and identifying reliability, safety, and process improvement opportunities.

Design, build, and operate low-latency, highly available distributed data systems and services to deliver high-quality data for algorithms and ML. Partner with data scientists and product teams to enable self-service data, real-time and batch processing, observability, and scalable multi-tenant solutions that run 24x7.

Lead design and execution of a modernized, Python-native AI/ML platform for AIMS: define architecture, drive migration, build migration tooling, ensure scalability, observability, cost optimization, and reliability, prototype GenAI operational tooling, and set org-wide technical standards.

Build and operate scalable, highly available ML/LLM serving and compute infrastructure. Own long-term platform vision, deliver zero-to-one projects, partner cross-functionally, optimize performance and capacity, and support production ML models at scale.