Deep Learning Engineer (Computer Vision)

About Us

RadiusAI is an early-stage startup that is helping brick & mortar retailers provide a level of experience that surpasses online experiences through AI and video analytics. Using AI we convert your live video into actionable intelligence using our cutting edge Viztel platform. RadiusAI is a US based computer vision analytics company providing real-time data to help create greater operational efficiency in health care, retail, and critical infrastructure. Radius AI technology features multi-camera tracking, real-time analytics, rapid, and cost effective, edge processing, and customized offers

About You

You are driven and passionate about data and making a difference. You are looking to join a promising early-stage startup to have a deep impact. You understand code quality and can take initiatives to improve it. You are always curious, and you are humble about what you already know.

About The Job

We are currently looking to hire data scientist with experience in cutting-edge data science and machine learning. We are particularly excited about candidates with experience (academia or industry) in deep learning, deployment of ML models, computer vision, large-scale machine learning, data filtering and augmentation, etc. We encourage publications at top-tier conferences, such as NeurIPS, CVPR, AAAI, etc.

You will work with state-of-the-art technologies in our data science team. You will be responsible for researching, developing, training, optimising and deploying machine learning models and analytic systems using ML models and algorithms.

Requirements
 Degree in a STEM field
 2+ Years of professional experience in Data Science / Deep Learning / Computer Vision.
 Knowledge of basic deep learning techniques
 Knowledge of modern software design and software engineering practices in Python
 Knowledge of of computer science fundamentals including data structures and algorithms
 Experience in data-driven problem-solving and the deployment of machine learning models
 Experience with cloud-computing tools, architectures and approaches
 Experience in working in a team and communicating to other data scientists and engineers

Pluses
 Experience in PyTorch and Tensorflow
 Experience in deploying ML-models at scale
 Experience in data filtering and augmentation
 Experience in data analysis tools and frameworks (pandas, numpy, matplotlib, etc.)
 Experience in data visualization, data introspection and dashboard design
 Experience with public cloud (AWS, Azure, GCP)
 Experience in distributed computing
 Experience in causal inference,