Senior Integration Engineer - Algorithms

We believe the future of our nation’s roadways is automated, safer, more accessible and enables more efficient movement of people and goods. While billions have been invested into developing vehicle technologies – including advanced driver assistance systems (“ADAS”) and autonomous driving solutions – a small fraction has been spent on developing infrastructure to support and enhance roadways. At Cavnue, we are developing and integrating technologies that will power the world’s most technologically advanced roadways (“cavnues”). Our approach is founded in creating a digital model of the roadway that analyzes and optimizes road conditions in real-time, sharing actionable alerts and providing proactive guidance to vehicles and drivers.

Join us in innovating the roads of the future. Cavnue is bridging vehicle technology and road infrastructure to rapidly deliver safer roads today while accelerating the adoption of connected and automated vehicles (CAVs) moving forward. With ongoing deployments in Michigan and Texas, Cavnue is the only company in North America that uses Smart Road technology to improve performance for road operators and deliver a safer, more efficient experience for all road users while preparing for a future with more CAVs. Our mission is to set the new standard for road performance and safety.

Role Overview

We seek an experienced Integration Engineer with a strong foundation in systems engineering and specialized expertise in classical algorithms for estimation and control, such as Kalman filtering. You will be responsible for designing, building, and maintaining robust services and integration solutions that incorporate real-time data processing and state estimation from various sensor inputs. This fully remote role involves collaborating with cross-functional teams to develop and deploy systems where accurate estimation and prediction based on classical methods are critical. Join us in building the foundational systems that power intelligent applications through sophisticated data interpretation.

Core Responsibilities:  

• Expert with Python and using technologies such as Postgres.
• Drive production of high-quality code through standards adoption, lifecycle testing, and continuous monitoring for opportunities to improve
• Engineer data structures, databases, and data lakes for optimal performance and reactivity in a production environment.
• Optimize algorithm implementations for computational efficiency, latency, and resource constraints, potentially targeting specific hardware or embedded systems.
• Integrate classical algorithm modules (potentially developed in C++ or using specialized libraries) seamlessly into the broader platform architecture and services.
• Build and manage scalable data ingestion, storage (e.g., data lakes), and processing pipelines optimized for ML training data and feature engineering
• Implement comprehensive monitoring, logging, and alerting for platform health, data quality, and algorithm performance.
• Collaborate closely with hardware engineers, software developers, and researchers on sensor selection, system architecture, calibration procedures, and resolving integration challenges.
• Maintain clear documentation for algorithms, system designs, integration points, and operational procedures.
• Assurance of high-quality code through standards adoption, lifecycle testing, and continuous monitoring for opportunities to improve
• Establish low-latency/high throughput APIs on streaming packets of data from the cloud and edge
• Contribute to a healthy and positive engineering culture

Nice to Have Responsibilities: 

• Work in a number of languages (Python, C++, Go), established libraries and technologies (Redis, BigQuery, Pulsar, Flink) and development environments (K8s, NVIDIA Jetson)  
• Experience with technologies like Apache Spark or Kafka
• Design, implement, and optimize algorithms for real-time state estimation and sensor fusion using classical techniques (e.g., Linear Kalman Filters (LKF), Extended Kalman Filters (EKF), Unscented Kalman Filters (UKF), Particle Filters, Bayesian estimation).

Requirements:

• 5+ years of professional experience in software engineering, platform engineering, or integration engineering.
• Bachelors Degree in Computer Science, Engineering or equivalent experience 
• Proficiency in programming languages commonly used for both platform development and algorithm implementation, such as Python and C++
• Experience with data analysis, visualization, and simulation tools (e.g., Python libraries like NumPy, SciPy, Pandas; potentially MATLAB)
• Experience with cloud platforms (AWS, Azure, or GCP) and core infrastructure services
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Excellent problem-solving, analytical, and troubleshooting skills
• Strong communication and collaboration skills
• Experience working with Git, GitHub, Jira, Confluence – or similar tools – including complex operations and workflows
• Comfortable working in a Linux development environment 
• History of building software in highly-collaborative environments
• Willingness and eagerness to think about how to solve problems for multiple users through common interaction patterns
• Experience designing practical and compelling architectures and systems
• You demonstrate curiosity and initiative to understand complex systems, with the ability to make meaningful progress independently and with minimal guidance.

Bonus:

• Early-stage start-up experience is a plus
• Worked in development of complex build processes and optimizing developer workflows
• Experience with Infrastructure as Code (e.g., Terraform, Ansible) and CI/CD pipelines

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: $145,000 - $195,000

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:

• Medical, dental, and vision benefits
• Life insurance and disability insurance
• 401(k) with 4% company contribution - no waiting period
• Parental and adoption leave
• Fertility and infertility benefits
• Wellness perks including access to on-demand primary care, virtual health appointments, and online mental health therapy
• Generous PTO bank, including paid year-end holiday shutdown
• Company-sponsored lunches twice weekly (in office)
• Learning and development opportunities
• Top-of-the-line equipment