לוח משרות דרושים Data Scientist משרה מלאה

Required Research Scientist - LTX Model Quality
The role
Following the success of LTX-2, our widely adopted open-source text-to-audio+video model, we are expanding our efforts to develop cutting-edge audio+video generation models and are hiring Research Scientists to join our LTX-Applications team.
As a Research Scientist in the LTX Model Quality team, you will play a key role in elevating the quality, controllability, and alignment of our video generation model. This role focuses on the critical post-training phase-developing and implementing techniques such as preference optimization, reward modeling, and human feedback integration to refine model outputs. You will design robust evaluation frameworks, define quality metrics, and build systematic approaches to identify and address model failure modes. Your work will directly impact the quality of the videos we generate.
What you will be doing
Develop and implement post-training pipelines, including RLHF, DPO, and other preference-based optimization techniques for video generation models.
Fine-tune and control VLLMs for video and audio understanding.
Design and iterate on quality evaluation metrics and frameworks.
Conduct systematic failure mode analysis and develop targeted interventions to address quality gaps.
Build and curate high-quality preference datasets and evaluation benchmarks that capture nuanced aspects of video generation quality.
Collaborate closely with fellow researchers to establish tight feedback loops between human judgment and model improvement.

Required Research Scientist - Audiovisual Understanding, Model Foundations
Team & role
The Core Generative AI team is a unified group of researchers and engineers dedicated to developing our generative foundational models that serve LTX Studio, our AI-based video creation platform. Our focus is on creating a controllable, cutting-edge video generative model by merging cutting-edge algorithms with exceptional engineering. This involves enhancing machine learning components within our sophisticated internal training framework, crucial for developing advanced models. We specialize in both research and engineering that enable efficient and scalable training and inference, allowing us to deliver state-of-the-art AI-generated video models.
As a Large Scale Video Understanding Research Scientist, you will play a key role in improving video generation quality and efficiency by improving video and audio understanding pipelines used for both training data construction and model evaluation.. This role demands hands-on work with large-scale Video Language Models (VLLMs), including fine-tuning, post-training, and control, alongside implementing classic computer vision and signal processing algorithms and applying strong research skills. Your expertise in post-training and controlling large scale foundational models, understanding statistics, implementing complex systems and eliminating bugs will be crucial, as our video training sets consist of petabytes of data processed across hundreds to thousands of virtual machines.
What you will be doing
Fine-tune and control VLLMs for video and audio understanding.
Design algorithms for balancing, filtering, and curating training and evaluation datasets, informed by model behavior and failure modes.
Implement classic and modern algorithms for processing, clustering, evaluation and filtering of large scale datasets.
Work within high-performance, scalable distributed systems capable of handling petabytes of data, with attention to throughput, correctness, and reproducibility..
Collaborate with other researchers and product stakeholders to iteratively improve training sets and evaluation protocols through tight feedback loops driven by model performance.

Required Research Scientist - Audiovisual Generation, Model Foundations
The role
Following the success of LTX-2, our widely adopted open-source text-to-audio+video model, we are expanding our efforts to develop cutting-edge audio+video generation models and are hiring Research Scientists to join our LTX-2 Core team.
Weve been at the forefront of innovation in text-to-image and text-to-audio+video generation, with LTX-2 driving our flagship product, LTX Studio, and gaining significant traction in the research and open-source communities, including integrations with platforms like ComfyUI and Diffusers.
This role focuses on pioneering model architecture and pre-training algorithms, shaping the next generation of our foundational generative AI models.
What you will be doing
Pre-train and fine-tune video, audio, and image generative models to pursue state-of-the-art results.
Publish papers and open source models to benefit the research community and advance the field.
Design and implement machine learning models for text-to-audio and text-to-video generation.
Collaborate with data engineers to curate and preprocess text and video data.
Optimize models for high performance, ensuring efficient training and inference.
Build new controls and capabilities into generative text-to-audio and text-to-video models.
Stay updated with the latest developments in Generative AI, particularly in the fields of image, video, and audio.
Work closely with product teams to integrate AI models into applications and services.
Conduct experiments and prototype new concepts to advance the capabilities of our AI tools.

Required Research Scientist - LTX Model Quality
The role
Following the success of LTX-2, our widely adopted open-source text-to-audio+video model, we are expanding our efforts to develop cutting-edge audio+video generation models and are hiring Research Scientists to join our LTX-Applications team.
As a Research Scientist in the LTX Model Quality team, you will play a key role in elevating the quality, controllability, and alignment of our video generation model. This role focuses on the critical post-training phase-developing and implementing techniques such as preference optimization, reward modeling, and human feedback integration to refine model outputs. You will design robust evaluation frameworks, define quality metrics, and build systematic approaches to identify and address model failure modes. Your work will directly impact the quality of the videos we generate.
What you will be doing
Develop and implement post-training pipelines, including RLHF, DPO, and other preference-based optimization techniques for video generation models.
Fine-tune and control VLLMs for video and audio understanding.
Design and iterate on quality evaluation metrics and frameworks.
Conduct systematic failure mode analysis and develop targeted interventions to address quality gaps.
Build and curate high-quality preference datasets and evaluation benchmarks that capture nuanced aspects of video generation quality.
Collaborate closely with fellow researchers to establish tight feedback loops between human judgment and model improvement.

we are looking for a Data Scientist.
The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage 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). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing:
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

We are looking for a strong, hands-on Data Scientist with knowledge in Security Research to join a cutting-edge AI and cyber security initiative at our company.
In this role, youll be part of a growing data science team working on advanced prevention technologies, leveraging vast amounts of data and state-of-the-art machine learning techniques to help protect users on a global scale.
This is a unique opportunity to join a high-impact, research-driven environment, where you will have the chance to shape core components of a next-generation security solution.
The team is responsible for researching and developing state-of-the-art AI/ML engines that protect hundreds of thousands of customers worldwide.
Perform daily analysis of real-world malware campaigns observed in the wild.
Research and evaluate optimal modeling approaches to address new security enhancements.
Design and build high-quality datasets and train models to detect emerging and advanced malicious techniques.
Deploy models within our companys cloud infrastructure, capable of processing and analyzing millions of files per day.
Key Responsibilities
Research and develop innovative AI-powered capabilities for cyber threat prevention.
Perform hands-on malware analysis in Windows environments, focusing on files and related threats.
Rapidly prototype and iterate based on data insights and user feedback.
Design and build data-driven solutions with a strong emphasis on practical impact and performance.
Collaborate closely with cyber researchers, analysts, and engineers to deliver production-grade machine learning models.
Work across organizational boundaries to bring solutions from concept to large-scale deployment, considering system constraints and integration challenges.

As an Applied Data Scientist, you will research, design, and implement complex algorithms that assess and monitor AI systems, including cutting-edge LLM applications. You will work in a high-paced environment where impact is key. You will collaborate closely with our engineering and product teams to push the boundaries of what automated AI evaluation can achieve, ensuring our users get the most reliable and actionable insights possible.

As an AI Solutions Engineer, youll partner with enterprise clients to understand their challenges and architect AI-driven solutions using the platform. Youll collaborate with leading data science and ML engineering teams, working alongside experienced practitioners to ensure smooth adoption and measurable business outcomes.

Youll design and deliver proofs of concept, lead workshops, and build compelling demos showcasing the capabilities of for AI evaluation, monitoring, and reliability. Acting as the key interface between our product, research, and customer teams, youll help translate technical requirements into impactful AI solutions.

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 our 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 in the board field of machine learning. 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 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 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 conferences and at leading journals
Actively identify new opportunities within our long term roadmap for applied science contributions.

Required Data Scientist, Product Analytics
As a Data Scientist, you will shape the future of people-facing and business-facing products we build across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining us, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and us. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Scientist, Product Analytics Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.

Required Data Scientist, Product Analytics
As a Data Scientist, you will shape the future of people-facing and business-facing products we build across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a varied set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining us, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Scientist, Product Analytics Responsibilities
Defining new opportunities for product impact Influencing product and sales to solve the most impactful market problems
Apply your expertise in quantitative analysis and the presentation of data to see beyond the numbers and understand how our users interact with our growth products
Work as a key member of the product team to solve problems and identify trends and opportunities
Inform, influence, support, and execute our product decisions and product launches in partnership with Product, Engineering, and cross-functional teams
Set KPIs and goals, design and evaluate experiments, monitor key product metrics, understand root causes of changes in metrics
Exploratory analysis to discover new opportunities: understanding ecosystems, user behaviors, and long-term trends Identifying levers to help move key metrics.

As a Data Scientist , you will be a part of a large and innovative data science group, working closely with Dev teams and product managers, to create business value through Data Science and Machine Learning methods using cutting edge technology, on large and diverse datasets.

The Role consists of understanding customers' needs and product requirements, exploring data, identifying and defining functionality from conception to delivery, creating and improving algorithms and ML pipelines, building measurement tools, providing data visualizations, and more.

Deliver end-to-end ML products - including data processing, problem analysis, research, model development, validation and metrics, implemented in production and with online testing.

Be a core member of a cross-functional AI innovation team, collaborating closely with software engineers, MLOps specialists, and analysts.
Design, build, and optimize end-to-end AI-driven features - from experimentation and model training to validation and deployment.
Develop production-grade code (Python and C#) to integrate advanced models and data-driven capabilities into our core products.
Continuously evaluate model performance and data quality in real-world settings, proactively driving improvements, retraining, and robust monitoring.

We are seeking an Analytics Functionality Analyst to join our Analytics engineering group. In this role, you will serve as a crucial partner to the Product Manager, facilitating the translation of complex analytics into actionable steps for functional software delivery. This hybrid position combines robust analytical skills with a keen understanding of engineering processes, allowing the Product Manager to focus on the strategic “what” and “why,” while you ensure clarity on the operational “how.” What you’ll do: Feature Translation: Convert high-level analytical concepts and product features into clear, functionally defined user stories that capture algorithmic and statistical nuances for the engineering team. Collaboration with Engineering Teams: Work closely with developers and data scientists to assess feature feasibility, identify edge cases, and establish thorough testing and validation criteria within the engineering environment. Customer Engagement: Participate in technical discussions with customers, especially when deep modeling insights or analytics expertise are required, to gather feedback that informs engineering decisions. Documentation Authority: Own the documentation of analytics functionality, positioning yourself as the internal authority on modeling logic and assumptions, thereby ensuring consistency and clarity across engineering projects. Support Engineering Testing: Drive the testing and validation of implemented models and features, ensuring they function as expected from an analytics perspective and contributing to overall product quality.

Position Intro:
Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.