Senior Machine Learning Engineer

What you get to do in this role:

SmartOps is an emerging technology group focused on bridging the physical world with the world of digital actions. We achieve this goal by extracting information from video cameras using edge AI technology and algorithmically trigger actions and workflows based on activity in the physical world. These digital actions eventually manifest as an activity in the physical world. The team is looking for talented machine learning engineers who can take theory to practice and make this vision a success.

Machine learning engineers are expected to find innovative and cost-effective solutions to key problems, deliver high quality code, improve model accuracy and model efficiency.

You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world.

• Build the best cloud-based AI/ML solutions to power intelligent enterprise services.
• Collaborate daily with a team of like-minded developers, product managers and quality engineers to produce quality software.
• Work with product owners to understand detailed requirements and own your code from design, implementation, testing and delivery of high-quality solutions to our users.

Requirements

To be successful in this role you have:

• A master’s degree in computer science with a major in Computer Vision algorithms.
• 4+ years of work experience applying computer vision techniques in an industrial use-case scenario.
• Strong in data structures and algorithms, software development skills in Python and C++
• Practical experience with runtimes and execution providers like ONNX, TensorRT, faster-transformer for NVIDIA GPUs.
• Practical experience with developing object detection and tracking algorithms and scaling inference for higher frame rates in production settings.
• Practical experience in designing/modifying/training one or more of Vision Transformer, YOLO, SSD, GAN, ResNET like models.
• Practical experience in data augmentation methods for object recognition and tracking use-cases.
• Strong understanding of AI quality evaluation metrics for object detection and tracking under various scene conditions.

Good to have:

• Strong understanding of model compression via parameter quantization, distillation, and shrinking techniques
• Experience in reading papers and implementing algorithms described in papers
• Knowledge of generative AI architectures for Image-to-Text, diffusion models
• Knowledge of video compression and streaming