Senior Machine Learning Engineer (Computer Vision)

Position Overview

We are seeking a Senior Machine Learning Engineer to join our growing Advanced Technologies team. In this role, you will design, develop, and deploy state-of-the-art computer vision and recommendation models that power our core products and solutions. You’ll tackle challenging problems in object detection, tracking, OCR, video analytics, and multi-modal systems while working in a dynamic, high-growth environment.

Key Responsibilities

• Design, develop, and deploy advanced computer vision models for real-world applications including object detection, tracking, OCR, image search, and scene understanding.
• Build and optimize deep learning models to ensure high accuracy, performance, and scalability in production environments.
• Explore and integrate multi-modal approaches by leveraging visual, textual, and other data modalities for robust solutions.
• Collaborate with cross-functional teams, including data and software engineers, to deliver end-to-end solutions.
• Lead the design and implementation of scalable pipelines for data processing, model training, and deployment.
• Optimize models for performance across various hardware platforms such as CPUs, GPUs, and edge devices.
• Conduct thorough experimentation and A/B testing to validate model effectiveness and align with business objectives.
• Mentor junior team members, providing technical guidance and fostering professional growth.
• Write clean, efficient, and maintainable code while adhering to best practices in software engineering and machine learning.

Required Qualifications

• MS or PhD (preferred) in Computer Science, Engineering, or a related field, or equivalent work experience.
• 5+ years of hands-on experience in machine learning and computer vision, with a strong track record of deploying models into production.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, ONNX, TensorRT). Experience with C++ is a plus.
• Strong experience with model optimization (e.g., quantization, pruning) and deployment on various platforms (cloud, edge, or mobile).
• Familiarity with cloud platforms (AWS, GCP, or Azure), containerization (Docker), and orchestration (ECS, Kubernetes).
• Proven experience in building and maintaining data pipelines (e.g., Airflow).
• Strong understanding of the agile development process and CI/CD pipelines and tools (e.g., Github Actions, Jenkins).
• Excellent communication skills, capable of presenting complex technical information clearly.
• Experience in high-growth, innovative environments is a plus.
• Publications in top-tier conferences (e.g., CVPR, ICCV, NeurIPS) are a strong plus.