לוח משרות דרושים Research Engineer

What We Are Looking For As a Red Team Specialist focused on GenAI models, you will play a critical role in safeguarding the security and integrity of commercial cutting-edge AI technologies. Your primary responsibility will be to analyze and test commercial GenAI systems including, but not limited to, language models, image generation models, and related infrastructure. The objective is to identify vulnerabilities, assess risks, and deliver actionable insights that strengthen AI models and guardrails against potential threats. Key Responsibilities
* Execute sophisticated and comprehensive attacks on generative foundational models and agentic frameworks.
* Assess the security posture of AI models and infrastructure, identifying weaknesses and potential threats.
* Collaborate with security teams to design and implement effective risk mitigation strategies that enhance model resilience.
* Apply innovative testing methodologies to ensure state-of-the-art security practices.
* Document all red team activities, findings, and recommendations with precision and clarity.

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact—whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection.

Hybrid:
Yes

We are seeking a Backend Engineer to join the development of ludeo.ai, our GenAI-powered product that enables users to generate interactive (gaming experiences) directly from prompts or video content. This is a high-impact role at the intersection of backend architecture, multimodal AI, and real-time systems. You will contribute to the AI engine that transforms unstructured inputs (text/video) into structured, interactive gaming playable moments.

What Youll Do

Design AI-Native Systems: Design and implement scalable microservices powering complex AI workflows. Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding strategies, and vector database infrastructure (e.g., Pinecone, Weaviate, Milvus, PGVector). Optimize retrieval, prompt orchestration, latency, and cost.
Agentic Workflows: Design and implement multi-agent systems using planner/executor/tool-calling patterns. Implement stateful, multi-step AI workflows with frameworks such as LangChain, CrewAI, AutoGen, or similar. Build evaluation, observability, and safety mechanisms for LLM systems.
Multimodal AI: Integrate multimodal models (vision + text) to understand video and translate it into structured form.
Scale & Infrastructure: Ensure robustness, security, and high availability on AWS/Kubernetes. Contribute to distributed systems that handle real-time data and AI workloads efficiently.
Collaborate: Work closely with Product and Design to translate GenAI capabilities into stable, scalable production features.

Were looking for a talented AI research team lead for the Data Science group, to help us develop advanced AI solutions that will empower impactful projects across. The Data Science group leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product, optimize processes, and deliver personalized experiences.
Lead a team of AI researchers
Manage and conduct advanced hands-on research projects that will impact 250M+ users
Leverage the latest advancements in LLM customization, multimodal models, knowledge representation, and conversational AI
Build horizontal AI capabilities to be used across
Collaborate with other internal departments to drive impactful data-driven projects.

We are looking for a talented AI Applied Researcher to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes.

What Youll Do

Lead an applied research for AI-driven features in the platform
Research and optimization agentic flows to solve complex problems
Collaborate with engineering teams to design, build, and maintain production pipelines
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques
Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.

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.