דרושים » תוכנה » Deep Learning Researcher

In this role, you will lead a team of Machine Learning Scientists and Engineers dedicated to building, training, and deploying cutting-edge Generative AI models. This includes developing foundation models trained on our companys extensive textual data and creating fine-tuned models designed to tackle complex travel-related tasks. Your leadership will play a pivotal role in advancing the application of AI to transform the travel experience for millions of customers.
As a technical manager, you should be passionate about GenAI technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML roadmap, and not be afraid to get your hands dirty with code when needed.
You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.
When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.
Key Job Responsibilities and Duties:
Leadership in LLM Development- Build, Guide and mentor a team of ML scientists and ML engineers in the development, fine-tuning, and deployment of large language models (LLMs) tailored for the travel domain.
Expertise in the engineering aspects of deploying LLMs at scale with minimal latency. This includes optimizing model performance, scalability, and efficiency to meet the demands of real-time, high-traffic applications.
Define and communicate the technical vision and strategy for LLM-related initiatives, ensuring alignment with company goals and customer needs.
Foster a culture of collaboration, innovation, and excellence within the team.
Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times.
Translate machine learning vision and strategy into planning and execution, and ensure timely delivery of their plans.
Develop innovative ML models, algorithms, and engineering approaches or identify existing ones, with the potential to impact our business.
Design and execute applied research plans to understand, apply, test, evolve, and generalize these technologies into reusable frameworks.
Translate business problems into viable, reliable and robust ML and AI solutions, accounting for constraints of the production environment.
Monitor product health, performance and business impact and act accordingly when requirements are not met.
Identify underlying issues and opportunities across domains and situations that are not obviously related through application of structured thinking and logic.
Solve issues by applying methods and insights gained from a variety of disciplines, navigating a variety of environments.

We are looking for experienced, creative and impact-oriented Algorithm Developers to join our team!
As an Algorithm Developer you will be responsible for building state of the art algorithms powering LLMs and agentic frameworks. You will be part of a multi-disciplinary team that also includes engineers and product professionals, all working together to bring our products to life.
You will take part in the full life cycle of our development process, deeply understand the problem we are solving, come up with algorithmic approaches for solving these problems, devise strategies for collecting necessary training data, train and evaluate large language models and other machine learning models and also be in charge of deploying these solutions in production.
Role and Responsibilities:
Build the algorithms that power our various products
Develop production-grade solutions to challenging product-driven NLP tasks by combining language models, RL and classical ML/NLP.
Collaborate with product, sales and customer success teams to define success criteria and translate them into quantitative measures and objectives
Devise innovative strategies for collecting training and evaluation data
Train and evaluate models in realistic production scenarios
End-to-end ownership of the algorithmic components of our products, from design, through implementation and monitoring in production

We are looking for experienced, creative and impact-oriented Algorithm Developers to join our team!
As an Algorithm Developer you will be responsible for building state of the art algorithms powering LLMs and agentic frameworks.
You will be part of a multi-disciplinary team that also includes engineers and product professionals, all working together to bring our products to life.
You will take part in the full life cycle of our development process, deeply understand the problem we are solving, come up with algorithmic approaches for solving these problems, devise strategies for collecting necessary training data, train and evaluate large language models and other machine learning models and also be in charge of deploying these solutions in production.
Role and Responsibilities:
Build the algorithms that power our various products
Develop production-grade solutions to challenging product-driven NLP tasks by combining language models, RL and classical ML/NLP.
Collaborate with product, sales and customer success teams to define success criteria and translate them into quantitative measures and objectives
Devise innovative strategies for collecting training and evaluation data
Train and evaluate models in realistic production scenarios
End-to-end ownership of the algorithmic components of our products, from design, through implementation and monitoring in production

Required Machine Learning Performance Engineer
Description
Our team is responsible for the AWS Neuron software stack, which powers Generative AI and other advanced ML workloads on AWS's custom-built ML accelerators Inferentia and Trainium. These accelerators deliver best-in-class performance and cost-efficiency for ML inference and training in the cloud.
We're building a new core group of engineers in TLV (Tel Aviv) to drive innovation in ML systems performance and software. As a Machine Learning Performance Engineer, you'll help shape the direction of the team from the ground up and work on:
Optimizing system performance across the entire ML software stack
Analyzing high-performance ML workloads running on Annapurna hardware
Developing high-performance kernels for critical ML operations
Enhancing the Neuron SDK to improve developer experience and system capabilities
Collaborating across Compiler, Frameworks, and Hardware teams to maximize end-to-end performance
As part of the Performance Engineering Team, you'll contribute to projects involving instruction scheduling, memory management, parallelism, kernel optimization, and compiler enhancements to maximize end-to-end performance.
This is a unique opportunity to be at the intersection of ML and systems within AWS, helping to build the future of AI infrastructure right here in Tel Aviv.
Key job responsibilities
Our engineers collaborate across diverse teams, projects, and environments to have a firsthand impact on our global customer base. You will:
Solve challenging technical problems, often ones not solved before, at every layer of the stack.
Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
Research implementations that deliver the best possible experiences for customers.
A day in the life
As you design and code solutions to help our team drive efficiencies in software architecture, youll create metrics, implement automation and other improvements, and resolve the root cause of software defects. Youll also:
Build high-impact solutions to deliver to our large customer base.
Participate in design discussions, code review, and communicate with internal and external stakeholders.
Work cross-functionally to help drive business decisions with your technical input.
Work in a startup-like development environment, where youre always working on the most important stuff.
Considering the technical requirements of this role, and to ensure fair and equal candidate consideration, we are conducting full interview loops. If you meet the basic qualifications, and the team is interested in moving forward, we will be in touch to coordinate your interviews.

our company was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at our company offers countless ways to make an impact in a fast growing organization. We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, Code Generation (PhD) (Tel Aviv) Responsibilities
Develop novel state-of-the-art computer vision algorithms and corresponding systems, leveraging various deep learning techniques.
Analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms. Perform state of the art research to advance the science and technology of Machine Learning and Artificial Intelligence.
Devise better data-driven models for information retrieval, Multi-modal fusion, generation or media understanding (CV, NLP, Speech/ Audio).
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Contribute to research that can be applied to our company product development.

We're looking for talented, versatile and highly independent Machine Learning Engineers to join our winning team. You will be in charge of end-to-end development and you'll have a massive impact on the product and the technical decisions made.
The ML Engineers are part of our infrastructure group, working closely with the exceptional research team, taking trained models and scaling them out to production.
Responsibilities
Take ownership of the entire machine learning engineering lifecycle - from building scalable training and evaluation pipelines to deploying models in production, with robust monitoring and maintenance systems.
Help in creating scalable solutions by enabling us to continuously increase the accuracy of our algorithms across thousands of clinics.
Designing a secured large-scale system that is suitable for sensitive patient data.
Continue to enhancing our deep learning infrastructure to supports our AI models at scale, including CI/CD, automation, testing and monitoring.
Collaborate with the research, medical and product teams in implementing ML solutions to the digital health space.

We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, signal processing, information retrieval, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, AI Core Machine Learning (PhD) Responsibilities
Develop novel state-of-the-art machine learning algorithms and corresponding systems, leveraging various deep learning techniques.
Analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms.
Perform state of the art research to advance the science and technology of Machine Learning and Artificial Intelligence.
Devise better data-driven models for information retrieval, Multi-modal fusion, generation or media understanding (CV, NLP, Speech/ Audio).
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Contribute to research that can be applied to our company product development.

Description
For many of us theres that one podcast we never miss, and video content is part of our daily routine, whether its professional or personal. But how many of us truly understand the effort that goes on behind the scenes? Here at our company, we know it well. Thats exactly why we built an AI-powered platform that helps content creators, podcasters, marketeers, and more at major brands like Netflix, Disney, Google, and Microsoft to create high-quality content with ease.
our companys technology streamlines the entire content creation process, turning ideas into professional-grade content with the highest production standards, without requiring expensive equipment or external services. The secret? AI-driven tools that replace traditional production roles like editing, directing, and design, automating the entire process at the click of a button.
About the Innovation Team
At our company, the Innovation team is all about pushing the limits of AI to transform content creation. We work on everything from enhancing audio and video quality to automating production with machine learning, NLP, and computer vision. Whether its real-time rendering, intelligent editing, or new ways to process media, we turn cutting-edge research into practical tools that creators rely on. If youre excited about shaping the future of media tech, youll fit right in.
On your day to day
Were looking for a seasoned and driven Team Lead to head our NLP & Speech team. In this role, youll lead a high-performing team of researchers and engineers developing state-of-the-art capabilities in real-time transcription, semantic understanding, content generation, and AI-powered editing tools. Leveraging our unique access to vast multimodal datasets and large-scale compute, your team will drive ambitious applied research projects from concept to deployment - powering intelligent, intuitive experiences for millions of content creators.
As a hands-on team lead, youll shape the technical roadmap for NLP and Speech at our company, identifying key opportunities to invest in foundational technologies and grow the team through strategic hiring and mentorship. Youll work cross-functionally with product, engineering, and design partners to ensure that advanced research translates into robust, scalable features that define the future of AI-assisted content creation.

As a machine learning scientist, your work will focus on building, training and deploying content models (Computer vision, NLP and Generative AI) using the most advanced technologies and models.
You will be responsible for identifying and proposing the most appropriate data sources and modeling techniques to solve complex problems and drive business value.
Key Job Responsibilities and Duties:
Explore and apply state-of-the-art techniques in multimodal machine learning.
Train innovative ML models (NLP, CV, LLM-finetuning), build algorithms, and engineering approaches to drive business impact..
Coding skills: ensure implementation of reusable frameworks (clean and scalable code).
Conduct data analysis with detailed metrics to evaluate models performance, labels quality, features exploration.
Work closely with machine learning engineers to ensure the model's latency/throughput meets product requirements and ensure deployment of your model to production.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

Central Applied Science (CAS) is a research and development team, working to improve our companys products, infrastructure, and processes. We generate real-world impact through a combination of scientific rigor and methodological innovation. Our focus is on longer-term, foundational work that addresses new opportunities and challenges across the company family of apps. The work we do enhances the company family of apps that enable billions of people to communicate with each other daily. Central Applied Science is interdisciplinary, with expertise in computer science, statistics, machine learning, and economics among many other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at our company and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise. We are looking for research interns to join the Product Algorithms team in Central Applied Science. The team is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally increase the magnitude of our companys successes. The ideal candidate will have extensive graduate training in computer science, machine learning, or related disciplines, and the passion to solve real world hard scientific problems. By applying your expertise and passion you will be empowered to drive impact across a range of products, infrastructure and operational use cases at our company. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, 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 our company's unparalleled data infrastructure.
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.