Sr. AI Engineer
Are you driven to make a profound, lasting global impact in artificial intelligence and real-time robotics? Look no further. Our Stealth Startup presents an unparalleled opportunity to take on exhilarating AI and ML challenges with a global reach. Join us today and embark on a transformative journey that revolutionizes the world of AI and Robotics. We are actively seeking passionate Senior AI Engineers who possess hands-on expertise in various domains, including real-time computer vision, robotics, generative AI, transformers, statistical machine learning, natural language processing, control/navigation, and reinforcement learning.
Candidates must have strong skills in machine learning (ML), deep learning (DL), robotics and real-time computer vision techniques. Candidates must also have hands-on ability to build ML/DL models that suit the problem, prepare datasets to test, evaluate the quality of models, and deploy them in production. Candidates must have knowledge and experience with containers, microservices architecture, and be able to independently deploy the ML models to production.
If you are a highly motivated individual with a passion for cutting-edge AI for robotics and multimodal perception, we would love to hear from you. Our company offers an unparalleled opportunity to tackle the most thrilling AI and ML challenges worldwide. Join our dynamic AI Engineering team as we deliver disruptive edge-compute systems capable of autonomous learning, prediction, and adaptation using vast real-time datasets.
We are at the forefront of inventing and expanding high-performance computing solutions for robotics, drones, self-driving cars, intelligent camera networks, assistive agents, and real-time monitoring and diagnostics. Our mission is to empower AI systems to interact with the complexities and uncertainties of the real world seamlessly and securely.
- Translating business requirements into requirements for AI/ML models, particularly those related to multi-modal perception and robotic applications.
- Preparing data to train and evaluate AI/ML/DL models.
- Building AI/ML/DL models by applying state-of-the-art algorithms, especially transformers. In some cases, leverage existing algorithms from academic or industrial research.
- Testing, evaluating the AI/ML/DL models, benchmarking their quality, and publishing the models, data sets, and evaluations.
- Deploying the models in production by containerizing the models.
- Working with customers and internal employees to refine the quality of the models.
- Establishing continuous learning pipelines for models with online learning or transfer learning.
- Building and deploying containerized applications on the cloud or on-premises environments
- MS degree (Ph.D. preferred) in computer science, machine learning, robotics, physics, computational science/engineering, or related technical field (or equivalent experience).
- 8+ years of work-related experience in software development with good Python, Java, and/or C/C++ programming skills. 5+ years in Machine Learning frameworks such as PyTorch, Tensorflow, ONNX Runtime, and TensorRT.
- Familiarity with containers, numeric libraries, modular software design (not including graduate school)
- Hands-on expertise with traditional statistical machine learning techniques as well as deep-learning and natural language processing modeling.
- Expertise in supervised, unsupervised, and transfer learning techniques.
- Hands-on expertise in machine learning techniques and algorithms with a strong background in state-of-the-art DNN architectures (Transformers, CNN, R-CNN, RNN, BERT, GAN, autoencoders, etc.) and experience in developing or using major deep learning frameworks (e.g., PyTorch, Tensorflow, etc.).
- Background with container technologies, such as Dockers and Kubernetes
Preferred Experience and Skills
- Demonstrable experience in building, programming, and integrating software and hardware for autonomous or robotic systems.
- Proven experience producing computationally efficient software to meet real-time requirements.
- Experience with solving and using machine learning for large-scale problems.
- Strong analytical skills with a bias for action.
- Strong time-management and organization skills to thrive in a fast-paced, dynamic environment.
- Solid written and oral communications skills.
- Ability to lead and mentor AI engineers and SDEs.
- Great teamwork and interpersonal skills.