Machine Learning Engineer - Computer Vision at CaseGuard

Arlington, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

15 May, 26

Salary

0.0

Posted On

14 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computer Vision, Machine Learning, Object Detection, Object Tracking, Video Segmentation, Facial Recognition, Deep Learning, TensorFlow, PyTorch, Transformers, Pandas, NumPy, SQL, Python, C++, MLOps

Industry

Data Security Software Products

Description

We are seeking a highly skilled and motivated Machine Learning Engineer specializing in Computer Vision to join our team. The ideal candidate will have a strong background in developing and deploying machine learning models focused on image and video processing. You will work closely with cross-functional teams to design, implement, and optimize vision-based AI solutions to address real-world challenges. Key Responsibilities: Design, develop, and deploy computer vision models for tasks such as object detection, object tracking, video segmentation, and facial recognition. Optimize and fine-tune deep learning algorithms for real-time performance. Work closely with the software engineers and product teams to identify opportunities for leveraging data. Collect, clean, and preprocess large datasets to prepare for model training and evaluation. Evaluate and optimize machine learning models for accuracy, performance, and scalability. Deploy models into production environments and monitor their performance to ensure reliability. Stay up-to-date with the latest advancements in computer vision and artificial intelligence. Collaborate with cross-functional teams to integrate machine learning solutions into business processes. Document processes, models, and implementations to ensure reproducibility and scalability. Required Qualifications: Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Experience in deep learning models, their training, and hyperparameter tuning using libraries such as TensorFlow, PyTorch, and Transformers or other Huggingface tools. Experience with data manipulation tools such as Pandas, NumPy, and SQL. Strong programming skills in Python and C++. Experience in MLOps principles and model deployment and instrumentation on cloud platforms such as AWS, Azure, or Google Cloud for model deployment and knowledge with efficient serving tools such as ONNX, triton, and vllm. Proficiency in working with image and video data, including preprocessing and augmentation techniques. Strong understanding of machine learning algorithms, including supervised and unsupervised learning and deep learning. Strong communication skills and the ability to work collaboratively in a team environment. Great to have: Familiarity with containerization and orchestration tools like Docker and Kubernetes. Experience with version control systems such as Git. Understanding software engineering best practices, including code review, testing, and documentation. Experience with Large Language Models (LLMs) is a great plus. Experience with data annotation tools and processes. Benefits: Competitive salary. Comprehensive health and wellness benefits. Professional development opportunities and continuous learning programs. Collaborative and inclusive work environment.

Responsibilities

The role involves designing, developing, and deploying computer vision models for tasks like object detection and tracking, while optimizing deep learning algorithms for real-time performance. Responsibilities also include collecting and preprocessing data, evaluating models, deploying them to production, and staying current with AI advancements.