Summary/Objective

As a Machine Learning Engineer specializing in Video Analytics within our Machine Vision team, you will research and develop models and algorithms that enable our cloud and IoT devices to decode streaming video and/or single frame inputs and generate interpreted output(s). You will also design and implement advanced computer vision algorithms, focusing on integrating cloud-based and edge-based Models into our cloud solutions. The ideal candidate will have extensive experience in developing machine learning and custom algorithms for video processing and other related computer vision domains in diverse computing environments.

Essential Functions

· Algorithm Development: Design, develop, and optimize computer vision algorithms for applications such as object detection, object classification, image segmentation and license plate recognition.

· Model Implementation: Implement and fine-tune deep learning models for computer vision tasks using frameworks such as TensorFlow and PyTorch.

· Edge Analytics: Develop edge-based solutions for real-time computer vision applications with limited computational resources.

· Cloud Integration: Create and manage high performance cloud-based computer vision pipelines.

· Dataset Management: Develop processes for data modeling, algorithm development, testing, and metric tracking to maintain end-to-end machine learning production workflows.

· Research & Innovation: Stay up to date with the latest advancements in computer vision, OCR, deep learning; review relevant literature to determine best approaches.

· Ability to operate independently on a small team in a startup-like environment

Education and Experience

· Bs/MS/Ph.D in Computer Science, Mathematics, Electrical Engineering, or a related field

· 5+ years of experience in computer vision and deep learning

· Strong programming skills in Python

· Expertise in computer vision libraries such as OpenCV and deep learning frameworks like TensorFlow and PyTorch

· Experience with cloud computing platforms (e.g., AWS) for deploying and scaling AI models

· Familiarity with edge computing and optimization techniques for resource-constrained devices

· Experience with version control systems (e.g., Git) and CI/CD pipelines

· Excellent problem-solving skills and attention to detail

· Strong communication skills and ability to work in a collaborative environment

Preferred Qualifications

· Experience with NVIDIA CUDA and GPU programming for accelerating computer vision algorithms

· Knowledge of MLOps practices and tools for managing ML model lifecycles

Key Technologies

· Cloud platforms: AWS SageMaker, Google Cloud AI Platform, Azure Machine Learning

· Edge computing: Intel OpenVINO

Job Type: Full-time

Benefits:

• 401(k)
• 401(k) matching
• Dental insurance
• Employee assistance program
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Referral program
• Vision insurance

Schedule:

• 8 hour shift
• Monday to Friday

Application Question(s):

• Will you require sponsorship?

Work Location: Remote