AI/ML Software Engineer
Artificial Intelligence
Automation
Data & Ai
Data Platform
Data Processing
Deep Learning
Developer
Edge Ai
Embedded
Embedded Software
Embedded Systems
Engineering
Grid Edge Technologies
Hardware Engineering
Hardware Software Co Design
Image Processing
Industrial Automation
Information Technology (IT)
Machine Learning
Machine Learning Engineer
Machine Learning Models
Machine Learning Pipelines
Machine Vision
Mechatronics
Nvidia Jetson
Nvidia Tensorrt
Object Detection
Onnx
Open Source Ai
Opencv
Openvino
Programming
Real Time Ai
Robotics
Software Development
Software Engineer
Software Engineering
Systems
TensorFlow
Video Processing
Job Description
Envision Technology, LLC is seeking an AI/ML Software Engineer to develop, adapt, and optimize image recognition capabilities for tactical use, with deployment targeted to embedded and edge hardware. The role emphasizes high-confidence computer vision performance that remains reliable in real-world operating conditions.
Responsibilities
- Assess, modify, and optimize existing image recognition algorithms, including object detection, semantic segmentation, and tracking approaches (such as YOLOv8, Mask R-CNN, and DeepSORT) for execution on embedded or edge computing platforms.
- Design and implement synthetic labeled training datasets to strengthen robustness across different environmental and operational conditions.
- Create synthetic imagery using physics-based modeling approaches, including illumination, material properties, sensor characteristics, and atmospheric effects, to better match actual optical sensor performance.
- Measure and validate model performance using quantitative evaluation methods such as precision, recall, confusion matrices, and confidence intervals to support deployment readiness.
- Partner with algorithm developers, hardware engineers, and system integrators to align AI performance with mission requirements and hardware constraints.
- Monitor emerging AI/ML methods and edge-deployment frameworks to improve efficiency and system capability.
Required Qualifications
- Bachelor’s degree in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or a related field.
- Proficiency with modern machine learning frameworks, including PyTorch, TensorFlow, and/or ONNX.
- Experience with computer vision libraries and tools such as OpenCV, NVIDIA TensorRT, and/or OpenVINO.
- Strong programming skills in Python and/or C++.
- Experience deploying models on embedded or edge hardware, including NVIDIA Jetson, Intel NUC, or AMD Ryzen Embedded.
- Ability to assess and refine algorithmic performance using quantitative evaluation techniques.
Technologies
- PyTorch, TensorFlow, ONNX
- OpenCV
- NVIDIA TensorRT, OpenVINO
- Python, C++
- NVIDIA Jetson, Intel NUC, AMD Ryzen Embedded
- YOLOv8, Mask R-CNN, DeepSORT
Desired Qualifications
- Master’s degree in a relevant discipline or 5+ years of applied AI/ML development experience focused on imaging, optical, or sensor-based systems.
- Background in optical physics, radiometry, or computer graphics-based image synthesis.
- Experience generating physics-based synthetic imagery using tools such as Blender, Unreal Engine, or custom rendering pipelines.
- Understanding of sensor modeling and the integration of physics-based parameters, such as MTF, SNR, contrast, and spectral response.
- Familiarity with MLOps tools for versioning, data curation, and training pipeline automation.
Benefits
- 401(k)
- Dental insurance
- Flexible spending account
- Health insurance
- Health savings account
- Life insurance
- Paid parental leave
- Paid time off
- Parental leave
- Tuition reimbursement
- Vision insurance
Additional Information
- Applicant must be a US Person.
- Candidates should have the aptitude and motivation to contribute proactively in a startup culture from day one and grow with the company.
- Brief travel within the US to customer locations may be required occasionally to support product testing or design reviews.
Job Details
- Job type: Full-time
- Work location: In person
- Location: Londonderry, NH (onsite)