Edge CV Engineer - Real-Time Vehicle Intelligence

GenLogs Corp.; New York (NY); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Healthcare (US based)

Unlimited PTO

Parental leave

401(k) plan

Travel reimbursement

Job summary

GenLogs is building real-time truck intelligence through a sensor network and AI-driven analytics. You will own computer-vision problems end to end, from camera placement to production deployment, ensuring reliable edge performance in harsh roadside conditions.

Join a team that blends ML rigor with engineering and field operations to deliver measurable improvements in freight visibility and safety. A strong CV background and edge hardware experience are essential.

Qualifications

• Minimum 4 years of professional experience in computer vision, data science, or research.
• Hands-on experience with applied computer vision techniques, especially on edge hardware.
• Proficient in Python, SQL, OpenCV, and PyTorch programming.
• Experience with Linux systems.
• Experience with Git.
• Strong problem-solving skills and attention to detail.
• Excellent written and verbal communication skills.
• Ability to communicate technical concepts to both technical and non-technical stakeholders.

Responsibilities

• Own computer-vision capabilities from initial problem definition through field deployment and sustained production performance.
• Build systems for vehicle detection, tracking, OCR, attribute extraction, embedding generation, and re-identification.
• Establish evaluation frameworks that connect model performance to successful vehicle identification and customer outcomes, not merely offline accuracy.
• Diagnose failures across the entire imaging pipeline, including camera placement, optics, exposure, lighting, encoding, training data, model behavior, edge compute, and downstream processing.
• Develop models and write the production software required to run them reliably at scale.
• Optimize multi-model pipelines for latency, throughput, memory utilization, and accuracy on constrained CPU and GPU edge hardware.
• Design experiments, analyze failure modes, and make clear decisions about what to improve next.
• Build monitoring and feedback loops that reveal model degradation, environmental shifts, hardware issues, and new failure modes.
• Work directly with field operations to test camera configurations and validate improvements under real roadside conditions.
• Partner with platform and data engineers while remaining accountable for getting your work into production.
• Improve annotation strategy, training datasets, and hard-example selection based on observed production failures.
• Evaluate new research, determine what is genuinely useful, and translate promising ideas into dependable systems.
• Raise the technical standard for computer vision across GenLogs through strong engineering, documentation, and mentorship.

Skills

Python

SQL

OpenCV

PyTorch

Geospatial data analysis

Tools

CUDA

ONNX

OpenVINO

TensorRT

Git

Linux

Job description

GenLogs is building real-time truck intelligence through a sensor network and AI-driven analytics. You will own computer-vision problems end to end, from camera placement to production deployment, ensuring reliable edge performance in harsh roadside conditions.

Join a team that blends ML rigor with engineering and field operations to deliver measurable improvements in freight visibility and safety. A strong CV background and edge hardware experience are essential.