לוח משרות דרושים NLP/Machine Learning משרה מלאה

Join the innovative NLP Capabilities AI group, to help build the next generation of awesome products and experiences using cutting-edge technology.

If you love having stretch goals, real-world challenges, and making customers incredibly happy while fostering your obsessive need for perfect code and user experience, this is the job for you.

Join our brand-new innovative team to help build the next generation of awesome products and experiences using cutting-edge technology.

In this role, you will:

Be a part of a vibrant team of Data Scientists and ML Engineers
Collaborate with many teams in Intuit and contribute to many components in different business units. We love engineers who lead the change, communicate with customers, and deliver the most beautiful and intuitive applications
Be expected to help architect, code, optimize, and deploy ML models at scale using the latest industry tools and techniques
Help automate, deliver, monitor, and improve ML solutions
Responsibilities
Design and build systems which improve machine learning scalability, usability, and performance.
Work cross functionally with product managers, data scientists, and engineers to understand, implement, refine, and design machine learning and other algorithms.
Effectively communicate results to peers and leaders.
Explore the state-of-the-art technologies and apply them to deliver customer benefits.
Interact with a variety of data sources, working closely with peers and partners to refine features from the underlying data and build end-to-end pipelines.

Come join Intuit's AI organization as a Data Science Group Manager, leading our NLP Capabilities group.
Responsibilities
Lead multiple teams of data scientists and machine learning engineers
Mentor and hire the best data scientists in Israel
Apply artificial intelligence, generative artificial intelligence, and machine learning techniques to solve complex questions or fuel new business opportunities
Deliver breakthrough benefits to Intuit users and customers, across small business and consumer products using individual, enriched, and aggregated data
Provide leadership in advanced engineering, data science, and analytics in the development of current and future products or technologies
Provide technical leadership across multiple teams, by understanding a key technology space deeply enough to help guide strategy
Provide and inspire data science innovations that fuel the growth of Intuit
Understand and teach proven methods and hacking skills in working with divergent data types at scale, to explore and extrapolate data-driven insights, using advanced, predictive statistical modeling and testing applied to data acquired and cleansed from a range of sources
Provide the entrepreneurial guidance essential for business stakeholders to appropriately interpret and build on findings, and fully exploit the insights revealed through the research

Our Tel-Aviv team develops machine-learning models that serve billions of buyers daily. To do so, we develop state-of-the-art recommendation and ranking systems. We work closely with domain experts to design features and embedding spaces best fitted for eCommerce. Finally, we use Meta's cutting-edge generative models to personalize the experience for our buyers.
Our team also builds AI capabilities to enhance Metas product catalogs to improve ads performance. Catalog-powered ads account for a significant portion of Metas revenue, with unlocking deep semantic understanding of our products being a key strategic lever for revenue growth.
If you're passionate about ML at scale and want to work with an amazing group of people - look no further - come and join us!
Software Engineer, Machine Learning Responsibilities
Leading projects or small teams of people to help them unblock, advocating for ML excellence
Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
Suggest, collect and synthesize requirements and create effective feature roadmaps
Code deliverables in tandem with the engineering team

We are looking for researchers and applied scientists to join the Central Applied Science team. Central Applied Science is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally contribute to Meta's success. By applying your expertise in quantitative methods, you will be empowered to drive impact across a range of products, infrastructure and company operations. Individuals in this role are expected to have expertise and publications within research areas including artificial intelligence, machine learning, statistics, causal inference and experimentation. The ideal candidate will have a passion for building data-driven products and forming research frameworks to solve challenging, real-world problems.
Research Scientist, Central Applied Science (PhD) Responsibilities
Work with vast amounts of data, generate research questions that push the state-of-the-art, and build data-driven products.
Develop novel quantitative methods on top of Meta's unparalleled data infrastructure.
Learn new tools, systems, and programming languages quickly as required by the particular project you are working on
Work towards long-term ambitious research goals, while identifying intermediate milestones.
Communicate best practices in quantitative analysis to partners.
Work both independently and collaboratively with other scientists, engineers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value.
Publish research results in top-tier conferneces and at leading journals
Actively identify new opportunities within Meta's long term roadmap for data science contributions.

We are using a variety of ML and stats models and algorithms, from classic supervised learning, to anomaly detection, unsupervised learning and semi supervised learning, to detect and mitigate ongoing fraud campaigns.

In our solutions we are using Graph Neural Networks, Ensembles, Boosting, Regression models, Time Series data, Causal Inference and more.
Software Engineer, Machine Learning (Tel Aviv) Responsibilities
Leading projects or small teams of people to help them unblock, advocating for ML excellence.
Develop highly scalable classifiers and tools leveraging machine learning, data, and rules based models
Suggest, collect and synthesize requirements and create effective feature roadmaps
Code deliverables in tandem with the engineering team

In Shop Ads, we personalize sellers' shops to delight our buyers' and satisfy their needs. From the products to the text and media that complement them, the layout that makes it most accessible - every decision has the buyer in mind.
Our Tel-Aviv team develops machine-learning models that serve billions of buyers daily. To do so, we develop state-of-the-art recommendation and ranking systems. We work closely with domain experts to design features and embedding spaces best fitted for eCommerce. Finally, we use Meta's cutting-edge generative models to personalize the experience for our buyers.
Our team also builds AI capabilities to enhance Metas product catalogs to improve ads performance. Catalog-powered ads account for a significant portion of Metas revenue, with unlocking deep semantic understanding of our products being a key strategic lever for revenue growth.
If you're passionate about ML at scale and want to work with an amazing group of people - look no further - come and join us!
Software Engineer, Machine Learning Responsibilities
Play a role in setting the direction and goals for the ML pillar, in terms of project impact, ML system design, and ML excellence.
Owning the entire development cycle, from ideation to realization across the stack. Designing and developing machine learning models using supervised, unsupervised, and deep learning techniques.
Implementing and testing machine learning models in a production environment
Take part in the overall team engineering efforts and contribute with hands-on work
Working with software engineers to integrate machine learning models into applications and systems
Collaborating with data scientists to identify and select appropriate machine learning algorithms and techniques

Be a part of a fast moving product team with a great track record of landing significant impact. The position will involve collaborating closely with product teams to capture our users intentions and applying tech skills to build end to end ML solutions that will drive performance and help better personalizing our ads experiences on top of Meta's state of the art ad systems. You will bring the ability to own the whole ML life cycle, define projects and drive excellence across teams. You will work alongside the worlds leading engineers and researchers to solve some of the most exciting and massive social data and prediction problems that exist on the web.
Machine Learning Engineer - Core Ads Ecommerce Responsibilities
Partner with product teams and other engineers to solve Shops Ads business problems through ML
Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence
Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate
Leading a team from a technical perspective to develop ML best practices and influence engineering culture
Be a go-to person to escalate the most complex online / production performance and evaluation issues, that require an in depth knowledge of how the machine learning system interacts with systems around it
Suggest, collect and synthesize requirements and create effective feature roadmap
Code deliverables that will tie the ML solutions you develop to our ad delivery stack

In this role, you will be researching and applying a range of software, computer vision and machine learning techniques for solving challenges that bridge virtual and real worlds and will impact billions of people. We're addressing a variety of technical challenges in the areas of real-time image processing, 3D graphics, SLAM, scene reconstruction, machine perception, visualisation and human interaction. As well there are opportunities to collaborate with researchers in Facebook Reality Labs (FRL) and Facebook AI Research (FAIR).
Computer Vision Engineer Responsibilities
Design and develop novel computer vision and/or machine learning algorithms in areas such as: real-time scene and object tracking, reconstruction and understanding as well as, segmentation, face tracking, body tracking, key point estimation, depth sensing, generative approaches such as GANs, 3D stereo and volumetric reconstruction, avatars, reconstructions and virtual try-ons.
Develop prototypes for future VR/AR/MR experiences, drive continued development, and integrate robust solutions into product.
Collaborate with cross-functional engineering and research teams from Facebook Reality Labs (FRL) and Facebook AI Research (FAIR)in computer vision, machine learning, and graphics.
Participate in cutting edge research in computer vision that can be applied to AR/VR product development.
Define projects for other engineers to possibly solve and achieve impact based on your direction

The Risk team in Financial Integrity is responsible for mitigating all fraudulent financial activity that is done in Meta products in order to drive trust and integrity for all people and businesses using Metas financial ecosystem, while accelerating growth.

Fraud prevention is one of Metas leading investment areas as part of the financial activity expansion in our portfolio of products. As part of this, we are supporting highly scalable systems that are able to support tens of billions of transactions per year.

The team is composed of software engineers, machine learning engineers, data scientists which are mostly seniors in developing state of the art backend systems, supervised and unsupervised machine learning models and our focus is to continue to lead industry standards in the FinTech space.
Machine Learning Engineer - Financial Integrity, Risk Responsibilities
Have a leading position in setting the direction and goals for the ML pillar, in terms of project impact, ML system design, and ML excellence.
Creating and fostering long term vision on building first class, state of the art fraud enforcement solutions
Owning the entire development cycle, from ideation to realization across the stack. Designing and developing machine learning models using supervised, unsupervised, and deep learning techniques.
Take part in the overall team engineering efforts and contribute with hands-on work
Working with software engineers to integrate machine learning models into applications and systems
Collaborating with data scientists to identify and select appropriate machine learning algorithms and techniques