Computer Vision Engineer

SR2 | Socially Responsible Recruitment | Certified B Corporation™; United States; On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Health, dental, vision and life ins.

Vacation and sick leave

401(k) and commuter benefits

Job summary

SR2 | Socially Responsible Recruitment | Certified B Corporation is seeking expert Machine Learning Engineers with deep experience in computer vision and deployment on low-cost embedded systems. You will design, train, and optimize real-time DL models for resource-constrained hardware, leveraging quantization, pruning, and hardware acceleration.

The role spans multiple levels from mid to staff/lead, offering challenging projects in embedded vision and edge AI across ARM, Jetson, and Qualcomm

Qualifications

• 5+ years in ML, DL, and CV.
• Experience deploying optimized DL models.
• Proficiency with Python and C++.
• Familiar with embedded platforms.
• Background in hardware acceleration.

Responsibilities

• Design and optimize CV models for real-time embedded systems.
• Apply quantization, pruning, and distillation for performance.
• Deploy ML models on ARM/NVIDIA Jetson/Qualcomm hardware.
• Write clean Python/C++ code with TensorFlow, PyTorch, ONNX.
• Develop SLAM, object detection, tracking, feature extraction.
• Collaborate with teams to integrate ML into production.
• Benchmark and profile models for latency and power.
• Research cutting-edge ML techniques for real-time performance.

Skills

Machine Learning

Deep Learning

Computer Vision

Python

C++

TensorFlow

PyTorch

ONNX

TensorRT

Model Quantization

Embedded Systems

Education

Master's degree

PhD

Tools

TensorFlow

PyTorch

ONNX

TensorRT

CUDA

OpenCL

Job description

I'm working with a company building the future of defense and industry through scalable autonomous products. They're backed by leading defense-focused venture capital.

Role Overview:

We are seeking expert Machine Learning Engineers with deep experience in computer vision, model optimization, and deployment on low-cost embedded systems. The ideal candidate will have a strong background in designing, training, and optimizing deep learning models for real-time applications. This role requires expertise in efficient neural network architectures, quantization, model compression, and hardware acceleration techniques to run ML models on resource-constrained devices.

We're hiring at multiple levels - mid all the way through to staff/lead.

Key Responsibilities:

• Design, develop, and optimize computer vision models for real-time applications on embedded systems.
• Implement model compression techniques such as quantization, pruning, and knowledge distillation to improve performance on low-power hardware.
• Deploy machine learning models on embedded platforms, including ARM, NVIDIA Jetson, Qualcomm, or custom ASICs.
• Write clean, efficient, and well-documented code in Python and C++, leveraging ML frameworks like TensorFlow, PyTorch, and ONNX.
• Develop and fine-tune SLAM, object detection, tracking, and feature extraction models for high efficiency.
• Collaborate with cross-functional teams to integrate ML models into production systems, optimizing for latency, accuracy, and power consumption.
• Benchmark and profile ML models to identify and implement optimizations for inference on embedded hardware.
• Research and apply cutting-edge ML techniques to improve real-time performance in resource-constrained environments.

Qualifications and Skills:

• Master's or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, or a related field.
• 5+ years of experience in machine learning, deep learning, and computer vision.
• Extensive experience in designing and deploying optimized deep learning models for real-world applications.
• Proficiency in TensorFlow, PyTorch, ONNX, TensorRT, and other ML frameworks.
• Strong experience with model quantization, pruning, knowledge distillation, and hardware acceleration techniques.
• Solid programming skills in Python and C++, with a strong understanding of software optimization.
• Familiarity with embedded platforms such as NVIDIA Jetson, Raspberry Pi, ARM Cortex, Qualcomm AI accelerators, or specialized AI chips.
• Experience with hardware-aware model optimization to maximize inference speed and minimize memory footprint.
• Strong problem-solving skills and ability to work independently on complex technical challenges.

Preferred Qualifications:

• Experience with real-time SLAM, visual odometry, and multi-sensor fusion.
• Knowledge of low-level hardware acceleration using CUDA, OpenCL, or specialized ML accelerators.
• Familiarity with robotics frameworks such as ROS for integrating ML models into robotic systems.
• Background in edge AI deployments and optimizing neural networks for mobile and IoT devices.

What We Offer:

It's a fast-paced, innovative, and collaborative startup environment, with a top-notch benefits package including:

• Top-tier health, dental, vision, short-/long-term disability, and life insurance, with full employee coverage and partial coverage for dependents
• Flexible/reasonable vacation and sick leave
• 401(k) plans, FSA, HSA, and commuter benefits