דרושים » AI » AI Researcher - Foundation Models & Generative AI - Base44

We are seeking a Senior Applied Researcher/ Data Scientist to join our core product organization, where you will build and deploy next-generation AI models powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). The role centers on building and scaling intelligent systems powered by LLMs, advanced ML techniques, and agent-based architectures.
You will join a team within our Cyber R&D organization, leading the companys core product portfolio-while driving AI innovation and setting best practices across the domain. The group focuses on developing next-generation technologies, including training and optimizing LLMs and building advanced multi-agent workflows, while mentoring data scientists across R&D.
As a key technical leader, you will guide the evolution of our AI capabilities-converting cutting-edge ideas into impactful, production-ready systems and shaping our long-term direction.
We are looking for visionary applied researchers eager to take on ambitious challenges and push the boundaries of AI in cybersecurity.
Responsibilities
Design and build advanced AI models and systems that power our core products and address real-world cybersecurity challenges.
Own initiatives end-to-end from identifying customer-driven problems and shaping solutions to experimentation, prototyping, and production deployment.
Drive forward new ideas and research directions, turning emerging concepts into practical, scalable solutions.
Influence the organizations roadmap and contribute to long-term technical strategy across our AI and product landscape.

At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we pioneered the world's first fully automated suite of AI-powered vehicle inspection systems, combining computer vision, machine learning, and generative AI. With over $380M in funding and strategic partnerships with Toyota, Amazon, General Motors, JLR, Volvo, and Hertz, our technology is deployed across manufacturing plants, dealerships, wholesale auctions, fleets, and seaports worldwide. Named one of Fast Company's Most Innovative Companies of 2026, our 300+ global employees are solutions-oriented, accountable, and driven by one shared goal: making roads safer for everyone. We are looking for an experienced Agentic AI Researcher to join the CTO’s office and help build the agentic backbone that automates work across UVeye, including R&D, product, sales, CS, marketing, finance, ops, legal, PM, and HR. In this role, you will partner with a small, senior research team to take agentic systems from idea to production, with direct visibility on company-wide impact. A day in the life and how you’ll make an impact
* Design and develop production-grade agentic systems that automate end-to-end workflows across UVeye’s business functions.
* Research and apply state-of-the-art techniques in tool use, planning, long-horizon reasoning, memory, and multi-agent coordination.
* Build robust evaluations, guardrails, and observability so agents are safe, measurable, and continuously improving.
* Partner with function owners to identify high-leverage automation targets, ship working agents, and quantify the workload reduced.

Required Applied AI Researcher- Sovereign AI Research
The Dream Job
Nations are waking up to a hard truth: critical intelligence infrastructure built on hyperscaler black boxes isn't a solution it's a dependency. The Sovereign AI Research Group exists to answer that differently.
We're not fine-tuning what already exists. We're rethinking the models architecture from the ground up modular, composable, and built with compute governance as a first-class design constraint, not an afterthought.
We operate under real-world constraints. The interesting problems live at the intersections of disciplines. That's where we operate.
This is a hands-on research role embedded within a team of senior researchers. Day to day includes training models, running benchmarks, synthesize data. The researchers you'll work alongside will challenge you technically and invest in your growth.
Responsibilities:
Open Research Tracks
Familiarity with at least one is expected:
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Train and evaluate models across research tracks, iterating fast while documenting rigorously.
Build and maintain benchmarking pipelines and evaluation suites.
Curate, structure, and preprocess datasets; contribute to synthetic data generation workflows.
Run ablations and controlled experiments to support research hypotheses.
Reproduce and stress-test results from recent literature relevant to the group's work.
Collaborate across tracks and with engineering teams through to production handoff.

Required Research Scientist - Sovereign AI Research
The Dream Job
Nations are waking up to a hard truth: critical intelligence infrastructure built on hyperscaler black boxes isn't a solution it's a dependency. The Sovereign AI Research Group exists to answer that differently.
We're not fine-tuning what already exists. We're rethinking the models architecture from the ground up modular, composable, and built with compute governance as a first-class design constraint, not an afterthought.
We operate under real-world constraints. The interesting problems live at the intersections of disciplines. That's where we operate.
Responsibilities
Open Research Tracks
We are hiring across the following specializations. We expect depth in at least one area and the intellectual range to collaborate across them.
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Define and execute a research within your track, experiments, quality gates, and upper bounds in rigorous manner.
Collaborate across tracks on system integration and cross-disciplinary research.
Collaborate work with engineering teams until production.
Mentor junior researchers and contribute to a culture of technical excellence.

We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate.
Key Responsibilities
Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale.
Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments.
Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems.
Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load.
Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand.
Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity.
Rapidlyזprototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves.
Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation.
Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era.
Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization.

Required AI Researcher - World Model
Description
Our breakthrough World Model technology combines aerial imagery with real-time ground views to build an accurate, rich representation of the vehicle's environment. As part of our World Modeling team, you will drive the next generation of AI-powered, cloud-defined vehicle technology-tackling ambitious research and turning cutting-edge deep learning into real-world solutions.
Responsibilities:
Research, design, and implement state-of-the-art deep learning models in computer vision (e.g., detection, segmentation, transformers, self-supervised learning).
Translate research into production-ready algorithms, writing clean, efficient, and scalable code in Pytorch.
Explore creative ideas, experiment with novel architectures, and continuously push beyond current SOTA.
Take ownership of your work end-to-end, from concept through prototyping to deployment in production.

We are seeking a remarkable master student researcher to join our CTO office research team. In this role, you'll take a major part in groundbreaking research projects focused on detecting and mitigating cyber-attacks on AI applications as well as traditional applications using advanced analytics and emerging AI technologies.

We're looking for a highly self-motivated individual who thrives on challenges, works both independently and in unique small teams, and can rapidly turn bold ideas to the next production-grade cyber security capabilities.

What will you do?
Take a major part in innovative research initiatives in AI, application and agentic security, addressing complex cybersecurity challenges.
Design and develop AI agents that extend our detection and mitigation arsenal.
Create novel cyber security solutions to counter emerging threats in LLMs, autonomous agents, and legacy systems alike.
Use modern AI models, means and development tools.
Drive projects end-to-end - from concept through production-ready implementation.
Collaborate with cross-functional teams to integrate new capabilities into our product portfolio.

Our work in Networking and AI is transforming the world's largest industries and profoundly impacting society. Our Networking product security team is looking for an outstanding technical AI red teamer with hands-on safety and security experience to help us improve the safety posture of AI models, systems and infrastructure. In this role you will reduce risk, threats, and vulnerabilities in our networking AI products.

What you'll be doing:
Drive hands-on safety and security research on a range of AI and networking products.
Develop tools and processes to expose novel weaknesses in AI models and systems to preempt threats.
Participate in defining and ensuring AI development processes meet safety and security standards.
Partner with cross-functional teams to understand needs and implement solutions.
Be a technical focal point across multiple teams and provide hands-on AI safety, security and engineering expertise.

We are looking for a GenAI & Competitive Intelligence Engineer to join our Competitive Intelligence team. This role combines deep technical expertise with a builder's mindset to design, implement, and maintain advanced AI-powered systems for automating knowledge collection, generating competitive insights, and ensuring broad internal knowledge sharing across the organization. You will spearhead AI solution projects from initial concept through execution and widespread adoption.
As a GenAI & Competitive Intelligence Engineer, you will
Main role: Build, implement, and maintain the AI-powered intelligence stack, using LLMs, agentic capabilities, MCPs, Skills, and advanced RAG, to automate data collection, analysis and sharing
Make knowledge impossible to miss inside. Build the competitive intel teams interfaces that get the right competitive insight to the right stakeholder at the right time
Drive projects from concept to execution to delivery
Evaluate and recommend ML and AI tools and frameworks to enhance productivity and effectiveness
Ensure the scalability and reliability of LLM-based system architectures
Engage with requirement gathering and product discussions with internal customers at JFrog
Be the focal point for collaborating with IS, IT and data science teams
Have solid understanding of various aspects of the software development supply chain, including DevOps, DevSecOps and MLOps, and conduct in-depth technical research around them.

Were looking for an AI Creative Gen- someone who lives and breathes visual creation and wants to redefine how video and stills are made. Think of this as the digital cinematographer of 2026. You dont just 'prompt'- you engineer multi-model workflows, integrate complex compositing techniques, and bridge disparate tools into a unified pipeline. You build, composite, and direct.
In your day-to-day, you will:
Own visual projects end-to-end - from receiving a storyboard to delivering high-end, cinematic video and stills using AI as your primary camera and studio
Direct the machine - apply your deep understanding of cinematography (lenses, lighting, camera angles, and composition) to guide AI models toward photorealistic perfection
Build & architect workflows - design and engineer hybrid production pipelines by integrating multiple models within WIVI. You will be responsible for orchestrating workflows that connect Midjourney, Image-gen models, and the latest video engines into a seamless output
Master the "non-AI" look - use VFX and compositing skills (After Effects/Premiere) to eliminate artifacts and ensure every frame feels intentional, grounded, and premium
Drive R&D through production - collaborate with the Motion Studio and Creative teams to solve high-complexity briefs. You dont innovate in a vacuum; you push the technical boundaries of AI within live projects, discovering new creative solutions and "impossible" workflows while executing at the highest level
Bridge the gap - combine AI-generated content with real-world photography or 3D renders to create seamless, high-fidelity brand stories.