Satis.AI is an early stage food tech company which uses deep learning-based computer vision, causal inference, and cognitive AI to change how we feed the people around the world. We are starting by providing software services to existing restaurant chains which use the live camera feed to provide augmentation for staff tasks with aim to help decision making, reduce error and cognitive load needed. This position us as the full stack AI operating system for autonomous kitchens. We are surfing on the opportunity created by the food delivery disruption to bring real technological innovation into kitchens and enhance both people's experiences as well as staff and environmental impact.

Our mission is to feed the world through our global food system which is more productive, resilient, more affordable, more sustainable, and healthier. A food system that provides accessible nutrition for everyone while preserving our planet. Satis.AI team includes people with extensive experience on the creation and deployment of scalable deep tech solutions as well as industry experts who share a passion for food, happiness and our world. That is where you come in.

We are hiring our initial extended team to expand the science and technology arms in Satis.AI. They will be responsible for developing the scalable and extendable product, which are utilised with the pilots we have with global restaurant chains. You will drive a specific agenda in a self-powered environment with autonomy, along with other brilliant members of the team, all passionate to make an impact. 

Joining a small startup team, you will create a lasting impact on the company and have the opportunity to shape culture and products around your vision and personality. You, being a core member of the team, will contribute to the most imperative parts of the product development process, which includes understanding client needs through research, conceptualising complex ideas into interactive prototypes, validating ideas through user testing, designing detailed high-fidelity interfaces, collaborating with the Engineering team to ensure high-quality implementation, and exhaustively testing the product to be confident that we’re shipping a product that meets all requirements.

The Role:

• Frame the clients’ challenges for the team to evaluate, suggest possible solutions and then help them deliver it in meaningful measurable smaller chunks.
• Defined procedure to Implement, test, and maintain machine learning methods through best practices and observability tools.
• Discuss and guide the team on train, analyse and report model performance.
• Define and evaluate tools for further automating research and analysis.
• Pushing the boundaries of current methods, by following and building upon the latest research in the context of object detection, classification and semantic segmentation, and proposing new methods.

On Offer:

• Competitive salary
• Strong equity
• Flexible-working
• Open to remote working
• 25 days holiday each year
• Paid sick leave for physical and mental health needs
• Unlimited fresh fruit, tea, coffee and healthy snacks provided
• Paid maternity, paternity, adoption or shared parental leave
• Pension

Working with us:

• Mission-driven - We are dedicated to bringing nutritious, environmentally friendly and most important of all, enjoyable food for all people around the world.
• Ambitious - We strive to be the best at what we do.
• Proactive and positive - We are pragmatic and self-driven. We iterate quickly, typically in 1-month cycles.
• Adaptable - We embrace change and uncertainty and work together to adapt to new situations.
• Flexible working - We have flexible working arrangements and encourage efficient work - not more work.
• Low ego culture - We are open to feedback and treat everyone with respect. We assume the best intent from others.
• Inclusive - We are open-minded and don’t just accept diversity - we celebrate it and support it.

As with any B2B organisation, the success of us depends on every member of staff being professional, amicable, and building strong relationships – both internally and with external stakeholders. Our ideal candidate traits are as follows:

• MSc or PhD in computer vision machine learning or relevant artificial intelligence deep learning field.
• Experience with tooling around running, managing and reporting on experiment (Neptune, wandb, mlflow, ...)
• Contributed and Experience in developing practical deep learning applications using detection architectures (Faster-RCNN, SSD, YOLO, EfficientDet).
• Solid theoretical understanding of machine learning and neural networks.
• Solid hands-on software development skills in Python (numpy, scipy, scikit-learn, OpenCV) and familiarity with C++.
• Ability to define objective and purposeful ways to measure progress, for meaningful small chunk of work which moved the team toward bigger objectives.
• Experience with delivering high-quality products based on industry-focused projects.