Job Description

Do you want to kick your career by working on brand new technologies and standards with global customers?
To be part of a small team with huge personal impact?

The Vision Business Unit (VBU) is a small and dedicated group in CEVA. We offer our customers the most specialized cores and algorithms to run any Computer Vision based application, including Machine Learning and Neural Networks. Areas such as Artificial Intelligence, Virtual Reality and Augmented Reality push us to deal with cutting edge technologies that our customers’ near future products require. The solutions are related to variety of markets such as Automotive, Smartphones, Drones, Surveillance and more.

The Machine Learning group at CEVA are developing algorithms that incorporate to the training stage so that Neural Networks will run better and more efficiently on CEVA’s AI cores. 
Our advantage is that we hold both HW and SW development in-house. This allows us to generate amazing products and see the full lifecycle from NN inception to real world applications.
Join us to create amazing products that bring AI to everyday products. 
We are looking for a talented deep learning algorithms researcher to join our Machine Learning group.

In this role, you will:

  • Take ownership for studying and implementing algorithms for training neural networks.
  • Design, test, and integrate new algorithms
  • Contribute to the team’s methodologies, share your work, and give/receive feedback from peers in the team
The best match…
  • B.Sc in Computer Science/Electrical engineering (MSc – an advantage)
  • 3-5 years experience in training neural networks (PyTorch – an advantage)
  • Experience in Computer Vision – advantage
  • Read and implement algorithmic publications in the field of deep learning, deduce product requirements, write a design sheet, and implement the algorithm
  • Develop new solutions for model compression and quantization – advantage
  • Hands-on experience in Python and C++
  • A Team player with good interpersonal skills

WSC Sports is the world’s fastest-growing sports-tech company, the developer of AI-based automation solutions for sports content creation and distribution, automatically and in real-time.

Why WSC-Sports:

Working with Great people in an awesome environment, using cutting edge technologies (video editing, AI, data, and sports- altogether!) with the opportunity to influence innovative products for NBA, Bundesliga, FIBA, Fox Sports, and other sports giants – are only part of the things WSC Sports has to offer!

What you’ll do:

  • Research and develop end-to-end real-time solutions for sports content automation using state-of-the-art deep learning algorithms for video, audio, and data analysis.
  • Full R&D cycle, from problem definition and research to implementation and productization with a high level of autonomy

What you’ll need:

  • MSc or Ph.D. in Computer Science, Electrical Engineering, Applied Math or related field with a focus on AI/Computer Vision/ML.
  • Theoretical and Hands-on experience with machine and deep learning solutions.
  • Experience in Computer Vision.
  • Strong analytical and problem-solving skills.
  • Excellent self-learning abilities.

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:

  • Research cutting-edge ML and causal inference methods and collaborate with leaders from academia.
  • Design platform components to solve real world action-taking problems.
  • Prototype new concepts.
  • Work with the world's largest enterprises on building action-taking policies.
  • Collaborate with product management to define new product features.
  • Collaborate with SW engineers to transform concepts into a product.

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.


  • PhD in CS, stats, physics or similar field, or MSc with 2+ years of experience. More extensive experience – an advantage.
  • Programming skills.
  • Background in causal inference or reinforcement learning – an advantage.

The Core Data Science team  at Facebook TLV is looking for a Research Scientist!

Core Data Science ( is a research and development team, working to improve Facebook’s products, infrastructure, and processes. We generate real-world impact through a combination of scientific rigor and methodological innovation. We are an interdisciplinary team, with expertise in computer science, statistics, machine learning, economics, political science, operations research, and computational social sciences, among other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address.

We are looking for researchers and data scientists to join the team in Tel Aviv. We work closely with various product groups throughout Facebook, bringing expertise in machine learning, statistics, causal inference, data analysis, and other quantitative methods. By applying your expertise in such topics you will be empowered to drive impact across a range of products, infrastructure and company operations. The ideal candidate will have a passion for building products and applying research expertise and the latest methods to solve challenging, real-world problems.

Research Scientist, Core Data Science Responsibilities
  • Build data driven solutions to mission critical inferential and decision problems by developing state of the art statistical and machine learning methods on top of Facebook's unparalleled data infrastructure.
  • Communicate best practices in quantitative analysis and develop cross-functional partnerships throughout the company.
  • Work both independently and collaboratively with other scientists, engineers, designers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value.
  • Actively identify new opportunities within Facebook's long term roadmap for data science contributions.
Minimum Qualifications
  • PhD in computer science, statistics, economics, or related quantitative field, or MS degree with 4+ years of relevant experience.
  • Experience using machine learning and statistical analysis for building data-driven product solutions or performing methodological research.
  • Experience in programming and data analysis using languages such as R or Python, with packages such as NumPy, SciPy, pandas, scikit-learn, tidyverse (dplyr, ggplot2, etc.).
  • Ability to initiate and drive research projects to completion with minimal guidance.
  • The ability to communicate scientific work in a clear and effective manner.
Preferred Qualifications
  • Publications in Machine Learning, statistics, data science, AI, computer science, or related technical fields
  • Experience in production level software development in Python or lower level languages such as C++, Java.
  • Experience in scalable dataset assembly / data wrangling, such as Presto, Hive or Spark.

About Us

Riskified is the AI platform powering the eCommerce revolution. We use cutting-edge technology, machine-learning algorithms, and behavioral analytics to identify legitimate customers and keep them moving toward checkout. Merchants use Riskified to increase revenue, prevent fraud, and eliminate customer friction. Riskified has reviewed hundreds of millions of transactions and approved billions of dollars of revenue for merchants across virtually all industries, including Wish, Prada, Aldo, Finish Line, and many more. We're privately funded and VC backed, and our recent Series E round raised $165 million with a valuation in excess of $1 billion. Check out the Riskified Technology Blog for a deeper dive into our R&D work.

About the Role

The Research and Data Science department is focused on bringing value to Riskified through the development of algorithms and analytical solutions. As a data scientist in the research department, you will be a valuable member of an innovative and technical data science team working on various problems. The department uses a wide variety of advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more).

The Chargeback Algorithm team is responsible for the Research behind Riskified’s core product. The team uses versatile methods (such as classification, clustering, ensembles) to optimize the performance of our models, and develops flows to support operational model training / validation processes and monitoring. We work in big-data settings (e.g. spark, kafka, etc.) using state-of-the-art environments (databricks). We are responsible for the design, research and development of these tools, hence part of our work includes writing production code.

What You'll Be Doing

  • Work to improve Riskified’s core product algorithm’s accuracy by implementing improvements to the ML flow
  • Research & implement improvements in our our decision engine algorithms
  • Work with Product & Dev teams to enhance processes and expedite model development life-cycles
  • Mentor team members in a variety of Data Science projects


  • 5+ years experience as a data scientist, applied researcher or similar in the industry
  • M.Sc/Ph.D in exact sciences
  • Experience in ML techniques & DS best practices
  • Deep theoretical knowledge in ML algorithms, solid understanding of statistics and applied mathematics
  • Extensive knowledge in classification problems of imbalanced data sets, including experience with boosting trees & ensembles
  • Ability to write clean and concise code, ideally in R or Python
  • Excellent communication skills with the ability to clearly explain complex concepts to business stakeholders
  • Creative thinker with a proven ability to innovate through data exploration and application of non-trivial solutions
  • Experience using Spark/Docker/Kubernetes and CI/CD – Advantage
  • Experience with Bayesian Optimization / Control systems – Advantage

Life at Riskified

We are a fast-growing and dynamic startup with 600+ team members globally. We value collaboration and innovative thinking. We’re looking for bright, driven, and passionate people to grow with us.

COVID-19 Update:

  • Our Tel Aviv team is currently working remotely. If anyone prefers to work in our office, we’re happy to offer an option to do so safely.
  • When the situation improves, we’re looking forward to adapting a hybrid of remote and in-office work for all our team members. We’ll be moving to a new space in TLV – check it out here!
  • We’re growing at a rapid rate and have transitioned our interviews to Zoom.

Some of our Tel Aviv Benefits & Perks:

  • Stock options for all employees, Keren Hishtalmut, pension
  • Private medical insurance, extra time off for parents and caregivers
  • Commuter and parking benefits
  • Team events, fully-stocked kitchen, lunch stipend, happy hours, birthday celebrations, yoga, pilates, basketball, soccer
  • Wide-ranging opportunities to volunteer and make an impact
  • Commitament to your professional development with global onboarding, skills-based courses, full access to Udemy, lunch & learns
  • Awesome Riskified gifts and swag!

Data Scientist

Causalis is a VC-backed startup partnering with the world’s leading pharma companies, building machine learning solutions to bring causal intelligence to healthcare. We are developing a platform of solutions based on novel and proprietary causal AI techniques, to help doctors, patients, and researchers understand and act on the cause-effect relationships in medical data. We are a multi-disciplinary, international team of experts in AI and ML, causal inference and data science, healthcare and medicine. We are looking for smart, driven and overall extraordinary individuals who are passionate about changing the world of personalized medicine, and eager to shape the future of Causalis.
We're looking for an experienced data scientist to join as one of the first members of the data science team, with the skills to take ownership from idea through implementation and deployment. You will be engaged in the early data exploration phase, health data engineering, development of causal models and other ML methods, evaluation techniques, and eventually product integration and follow-ups — the essential challenges to make Causalis deliver ML solutions.
How you’ll contribute:
  • Apply state-of-the-art methods in health research to improve and validate our ML and data science capabilities
  • Define, design, and execute data engineering and ML tasks with a high bar for quality and robustness
  • Collaborate with infrastructure engineers to design and implement data pipelines end-to-end with complex data types to fuel ML experiments
  • Work with internal and external domain experts to define and execute the needed solutions in healthcare
Our ideal candidate will bring:
  • 4+ years of experience working as a data scientist
  • Strong experience with ML and data science in research and production environments (ideally with causal inference methods)
  • Strong Python skills
  • Excellent communication skills and ability to work with technical and non-technical partners from many teams
Nice to have:
  • Experience working in the healthcare industry
  • Deep knowledge of data-driven research in healthcare
  • MS/PhD in a relevant engineering or science field
  • Experience with ML explainability methods
  • Strong experience with NLP
  • Experience with imaging data
  • Experience with genetic data

Localization and detection algorithms such as YOLO have changed the world by enabling a precise detection and classification in a fraction of time needed before. However it's challenging to implement those methods in a changing environment like in many industrial cases. Therefore, we will look into different techniques and methods to increase sample efficiency using prior knowledge in order to achieve a single-shot localization algorithm. During the internship you will check whether CAD information can increase sample efficiency, make better localization, and many more questions.

We are looking for Senior Researcher for applied Machine Learning and Data Science in the Research & Innovation team at Our solution uses machine learning and AI to help people and companies to have better conversations. It is used by tens of thousands of people to improve their skills, help managers and team mates to coach, share information and facilitate better meetings.
As a Senior Researcher, you’ll join a team of experienced researchers, building Machine Learning features that power the Chorus platform. These include improving our in house Speech Recognition, Speaker Separation, Image Understanding and Indexing, NLP features and data science analytics.
This position is hands-on and requires programming skills (we write production grade code), ML understanding and the ability to learn new skills and frameworks (PyTorch, Kaldi, Spacy, and in general whatever works).

What You Will Do:

    • Help customer-facing positions communicate better, by turning unstructured human conversations into actionable predictions and coaching opportunities.
    • Translate business problems into Machine Learning projects, brainstorm to identify the best approach, and conduct hands-on research to weave together data, product thinking, and algorithms to generate business value.
    • Write production-grade code that serves top brands.
    • Continuously evolve and help others evolve professionally, through joint work and mentoring, staying up-to-date with the latest ML developments.
    • Use the generated data to produce impactful insights for our customers.

What You Bring To the Table:

    • Experience in ML, NLP, Vision or data science
    • Excellent business understanding and communication skills
    • Intimate familiarity with a variety of Machine Learning disciplines and algorithms
    • A PhD or Master degree in machine learning,  data analysis or statistics research
    • Experience in the industry of 3+ years
We are looking for candidates who are passionate about achieving a deep understanding of the problems domains, creating solutions that work and working with engineering to deploy them.

AI Research Engineer


Our team’s mission statement:

The AI team at SparkBeyond is responsible for building and continuously enhancing the core research engine powering the SparkBeyond AI-powered automated data science and research platform. We plan, design, and perform unique research that brings our product to life, leveraging our experience in Machine Learning and AI.

We continuously strive for making significant breakthroughs, providing our clients with a best-performing, one-of-a-kind product that solves fundamental, real-world problems across countless industries and domains.

What will you do?

  • Build the next generation AI-for-Data-Science technology using cutting-edge software, algorithms, methods, and practices.
  • Bring your novel ideas from the drawing boards all the way to production, creating the optimal experience for our users and enabling them to make revolutionizing breakthroughs and discoveries.
  • Use your analytical skills and curiosity for researching NLP, Data Mining, Machine Learning & Deep Learning.
  • Working with endless kinds of data from various industries including medical, energy, and retail, and using it to solve some of the world's toughest problems.
  • Interface with many other teams – infrastructure and full-stack developers, QA, data scientists, UX, and others.

What will you need?

  • 3+ years of hands-on, software development experience in Scala, Java, or C#.
  • MSc or higher academic education in computer science or related fields (applied mathematics etc.).
  • Strong analytical and research skills and experience working with data.
  • Hands-on experience with Machine Learning techniques (classification, regressions, feature selection, etc.).

ML CV developer


For a new startup in the field of computer vision and deep learning, a ML computer-vision developer is needed to own the development of a robust end-to-end deep learning computer vision product.

Availability is required for about 50% capacity in the next 3-6 months.

We are looking for a person experienced with SOTA computer vision deep-learning architectures, who will implement the network architecture, training and evaluation. You will be expected to participate in research and design of all stages of development, including dataset creation and up to convergence, integrating hand-crafted features, overcoming domain-specific caveats on the way until successful delivery to production.


  • Experience with deep learning frameworks in Python.
  • Experience with computer vision objectives and related deep-learning architectures.
  • Advantage – experience in dataset generation and augmentation.
  • Advantage – experience with delivering deep learning products to successful production level.
  • Advantage – experience in working against the cloud (e.g. AWS, GCP).
  • Advantage – familiarity with classical image processing techniques.
  • Advantage – BSc or higher degree in computer science / math / related subject.
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