Remote High Performance Computing Jobs in Belleville, MI

Cavnue, a Consor company, is redefining what's possible for modern transportation infrastructure. As the digital infrastructure platform within Consor Engineers, a leading North American engineering and advisory firm, Cavnue combines advanced roadway technology with deep transportation design and delivery expertise to modernize how roads are operated and managed.

We believe the future of roadways is connected, intelligent, and designed to actively improve safety, efficiency, and accessibility for all users. While vehicle technologies such as advanced driver assistance systems and automated driving continue to evolve rapidly, roadway infrastructure must evolve alongside them. Cavnue is closing that gap by developing and deploying smart road technologies that deliver a real-time digital twin of the roadway environment, leveraging AI-enabled analytics, sensors, cameras, and integrated digital infrastructure to provide actionable operational insights.

Together with Consor, we are accelerating the deployment of these solutions at scale, helping public and private clients modernize infrastructure and prepare for the next generation of mobility. With active projects across the United States, our work is setting a new standard for roadway performance today while laying the foundation for a safer, more efficient, and more connected transportation future.

Join us as we shape the future of infrastructure where digital innovation meets engineering excellence to deliver measurable real-world impact.

Role Overview

We are looking for a versatile generalist Senior Software Engineer, for our Core Software team, with a strong foundation in high-performance computing who excels at building and operating real-time systems. This is a hands-on role focusing on the core internals of our platform, including building low-latency communication between applications, integrating object tracking algorithms, ensuring reliable data flow from edge devices, and preparing data for AI model inference and classification.

You will be expected to implement production-ready, product-facing algorithms directly in C++, and you must understand how to rigorously iterate and build off of historic and simulated data to validate these systems before they hit the real world. Our architecture centers on strong API interfaces, requiring strong data interface knowledge to ensure robust communication. This is supported by a stack including PostgreSQL for persistence and Terraform, Helm, and Argo for infrastructure and deployment.

This is a fully remote, hands-on individual contributor role with meaningful ownership across core systems. We need a true self-starter who handles ambiguity well. You will be expected to take high-level requirements and run with them end-to-end—from initial implementation to production deployment and ongoing Operations & Maintenance (O&M). You think beyond the code, connect your work to the broader product, and use AI-assisted tools thoughtfully to move faster without compromising quality.

Core Responsibilities:

• Handle ambiguity as a self-starter, taking raw requirements and translating them into robust system design and implementation.
• Take complete ownership of the feature lifecycle, driving it from initial development through production deployment and ongoing O&M (Operations & Maintenance).
• Design, build, and maintain high-throughput, low-latency C++, Go, and Python services, for core platform components.
• Iterate and build upon historic and simulated data sets to thoroughly test, tune, and validate algorithms before deploying them to live, real-time environments.
• Demonstrate strong data interface knowledge by designing and implementing high-performance inter-application communication protocols for real-time data exchange.
• Design and optimize data structures, Protobuf serialization, and Redis Streams for real-time data processing workloads.
• Architect and manage data pipelines from raw sensor ingestion to transformation, storage, and delivery.
• Design, implement, and integrate complex, high-performance product-facing algorithms, including tracking, inference, and sensor fusion directly into C++ and Python production services to deliver real-time insights and inferences.
• Develop REST APIs and internal/external service integrations.
• Implement and enhance deep system observability, monitoring, logging, and alerting for performance-critical C++ and Python applications.
• Operate containerized services on Kubernetes (using Argo and Helm) in GCP; document systems, runbooks, and integrations.
• Contribute to a healthy, high-trust engineering culture where good ideas can come from anywhere.

Nice to Have Experience:

• Domain experience in transportation, robotics, autonomous vehicles, or sensor-heavy systems.
• Familiarity with classical estimation and filtering techniques, including Kalman filters, Bayesian methods, and sensor fusion, sufficient to read, integrate, and debug implementations.
• Experience with GCP data products (BigQuery, Cloud Storage, Pub/Sub) and AI/ML workflows, feature stores, or model serving infrastructure.
• Familiarity with messaging and observability tools such as nanomsg and OpenTelemetry.
• Experience with high-throughput data processing techniques and integrated build systems like Buck2.
• Prior experience in early-stage startup environments.

Requirements:

• 5+ years of professional software engineering experience as a generalist with a strong backend and systems focus.
• Deep experience building, tuning, and operating real-time systems.
• Strong proficiency in C++ is highly preferred, with proven experience implementing high-performance, low-latency algorithms in production. Proficiency in Python for prototyping is preferred.
• Proven ability to utilize historic and simulated data to rapidly iterate on algorithms and system logic.
• Strong data interface knowledge, including experience with inter-process communication (IPC), high-speed messaging protocols, and designing strict, robust interfaces for communication between applications.
• Deep expertise in algorithms, data structures, and system internals; able to reason about computational complexity, memory constraints, and system behavior under load.
• Experience building and operating streaming data systems (e.g., Redis Streams, Kafka, etc.).
• Experience with scientific/numerical Python libraries (NumPy, SciPy, Pandas), GCP (or comparable cloud infrastructure), containerization (Docker/Kubernetes), and Infrastructure as Code/CI/CD pipelines (Terraform, GitHub Actions, GitLab CI, etc.).
• Comfortable working in Linux and with agentic coding tools (e.g., Claude Code, Cursor, or similar AI-assisted environments).
• Strong communication skills to explain architectural decisions clearly to both technical and non-technical stakeholders.
• BS in Computer Science, Engineering, or equivalent practical experience.

Salary Range: The compensation range for this position is specific to the location(s) listed below and is the range Cavnue reasonably and in good faith expects to pay for the position taking into account the wide variety of factors that are considered in making compensation decisions, including job-related knowledge; skillset; experience, education and training; certifications; and other relevant business and organizational factors. Actual pay may vary based on these factors and geography.

Remote - $150,000 - $200,000

Additional Compensation: The successful candidate may be eligible to participate in Cavnue's equity program and/or a discretionary annual incentive program, subject to the rules governing such programs. (Cash or equity incentive awards, if any, will depend on various factors, including, without limitation, individual and company performance.) Note: Cavnue's benefit, compensation and incentive programs are subject to eligibility requirements and other terms of the applicable plan or program.

Benefits:

• Eligible employees may participate in a benefits program that may include:
• Medical, dental, and vision benefits
• Life insurance and disability insurance
• 401(k) with company contribution
• Paid Parental leave
• Fertility and infertility benefits
• Industry-competitive PTO
• Learning and development opportunities

Benefits are subject to eligibility requirements and the terms of the applicable benefit plans and programs.

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