We’re looking for an experienced data scientist with a strong background in modeling and model evaluation to help us develop and optimize our core algorithms for AI Assurance. Superwise’s solution offers practical capabilities to monitor ML models and gain insights into their behavior in a live production environment. Our mission is to help data science teams to scale their AI effectively.
As a data scientist you’ll develop and optimize algorithmic solutions for complex, real-world problems in a wide variety of use cases like models performance management, optimization, anomaly detection, bias detection, explainability and more, across multiple industries (fintech, marketing, gaming, etc.). You will also take a critical part in our thought leadership efforts by initiating and collaborating on pieces of content and other articles to help educate the data science and MLOps community.
Requirements
Nice to have:
The Opportunity
Vianai is hiring a data scientist to join our team and take part in the design and development of a business action optimization platform based on causal ML and reinforcement learning.
This is a unique opportunity to play an early, significant role in building an impactful product, in a positive and challenging environment.
You will join an exceptionally strong team from the industry and the DS community including access to most F500 companies and ample funding.
What you’ll do:
About you:
You’re perpetually curious. You’re excited about new ideas and research and about applying them to make an impact. You have excellent hands-on data exploration and coding skills.
You’re independent as well as a team player and you’re looking forward to collaborating with customers and colleagues.
Qualifications:
UVeye is looking for a Computer Vision Algorithms Engineer. As a Computer Vision Algorithms Engineer you will take part in the development and implementation of new Computer Vision and Machine Learning technologies.
Responsibilities:
UVeye is looking for a Machine Learning Software Engineer to join our ML Team. In this role, you will develop efficient and scalable code to create and operate ML systems for our production and Infra environments
Responsibilities:
Description
We are making the future of Mobility come to life starting today.
Our vision at Autofleet is to create the first, truly sustainable, Vehicle as a Service layer,
providing an elastic supply of vehicles serving any source of demand.
We are a startup funded by industry leading investors and are looking for the best people to partner with and shape the company, product and technology moving forward.
Autofleet’s data scientists are responsible for researching, developing and maintaining machine learning models and optimization algorithms as well as data infrastructure and pipelines that power autofleet’s Vehicle as a Service platform for optimizing large scale fleets.
As a data scientist in autofleet you will work directly with engineers, sales, product and clients in order to translate business requirements to production level prediction models and algorithms.
Position based in Tel Aviv.
What You’ll do
Requirements
At Sight Diagnostics, we aim to improve health through fast and accurate diagnostic testing. We have successfully built our Sight OLO device which performs complete blood count (CBC) based on our own scanning hardware, computer vision and machine learning algorithms. We are now building on our vast experience to extend our capabilities to new and exciting sample types and clinical conditions.
The Data-Scientist role will be part of the Algorithm R&D team.
This role requires a combination of strong R&D capabilities, hands-on approach and good coding skills.
We are looking for someone who is interested in a real challenge, inclined to constant innovation, and excited about contributing to the forefront of medical diagnostic technology.
In your role as Data-Scientist, you will:
About You (skills, experience, potential)
We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.
About Sight:
Our Work : Founded in 2011, Sight DiagnosticsⓇ aims to transform health systems and patient outcomes through accurate and convenient blood diagnostic testing. Sight’s technology, developed over almost a decade of research, represents breakthrough innovations in diagnostic methodology. Sight’s latest blood analyzer, Sight OLOⓇ, performs a Complete Blood Count, the most commonly ordered blood test, with only 2 drops of blood from a fingerprick or venous sample in minutes.
Our Culture: We are a team of passionate problem solvers who are committed to the social impact our technology represents. We enjoy tackling big, complicated and important technological, clinical and behavioral-change challenges as a team, and we succeed through cross-disciplinary collaboration across a non-hierarchical structure. Sight is where everyone’s ideas are valued, considered and debated. We insist on a healthy work-life balance and support working parents with flexible working hours.
Our People: Sight is a rapidly growing team of over 100 individuals, working together on a common mission. We value diversity and are proud of the different professions, backgrounds, expertise and beliefs that make up Sight’s unique ways of thinking. Our people are united by two shared qualities: being exceptional at what they do and caring deeply about making positive changes in the world.
Brodmann17 is a provider of software-only perception technology for vision-based automated driving. Brodmann17’s patent-pending deep learning architecture delivers state-of-the-art accuracy while consuming only a fraction of the compute power, expanding the benefits of artificial intelligence found in premium vehicles to the mass market. Brodmann17’s solution is built from the ground up and designed to meet the industry’s toughest standards for the world’s largest automakers and Tier-1 automotive suppliers. Three years into the research and the technology has its first design wins with automotive companies whose products are expected to hit the market as early as this year.
If you want to work in one of the most interesting AI companies led by top technologists and researchers in this field – join us!
About the Job:
We are seeking an experienced and sharp algorithm manager with a solid understanding in Deep Learning and Computer Vision that will help shape the future of computer vision solutions and lead our research team.
Main Responsibilities:
Required
Big Advantage:
This is us
Artlist is a leading Creative Technology company for video creators. With original, high-quality music, SFX and footage, Artlist is helping creators produce quality content worldwide.
Since being founded in 2016, Artlist has managed to revolutionize the Filmmaking industry by offering subscription-based products with a license that covers every video project from personal use to commercials with high quality curated content
Today, Artlist is the go-to licensing provider for content creators in over 160 countries.
Our company continues to grow in search of new solutions that will simplify the workflow of filmmakers and creators, so they can focus on creating quality content.
We are looking for a Senior Data Scientist to join our data science team in Tel Aviv.
As a data scientist you’ll define, research, develop and deploy models – impacting artists and creators all over the world!
Working with us means training your model on diverse data created by the top filmmaker and musicians worldwide (you’ll love it!)
Wake up for this:
Requirements:
Cynet is a technology-oriented company continuously looking for new ways to innovate the Cybersecurity world. Our main priority is to defend our customers from any harm in the vast digital ocean. But Cynet is more than just a product, we are a family. We value each one of our members and their inputs. Cynet is a place where your work will have a direct impact on the way we service our customers.
We are looking for a passionate hands-on Data Scientist to join our research team and develop new innovative machine learning ideas from conception to realization based on our multi-vector diverse datasets.
Some of the challenges you will tackle:
Would be great to also have: