דרושים » מדעים מדוייקים » Senior Applied Researcher- AI Research

We are seeking a Senior AI Engineer to join core product organization, where you will design, build, and scale next-generation AI systems powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). This role focuses on developing production-grade systems leveraging LLMs, advanced machine learning, and agent-based architectures.
You will join a team within Cyber R&D organization-leading the companys core product portfolio- while driving AI innovation and establishing engineering best practices across the domain. The team focuses on building and optimizing large-scale AI systems, including LLM-based solutions and advanced multi-agent workflows, working closely with data scientists and researchers to bring ideas into production.
The Responsibilities:
Design, build, and own end-to-end AI solutions- from data collection and preprocessing to model training, evaluation, and production deployment.
Optimize systems for performance, scalability, and reliability in production environments.
Collaborate closely with product, design, and engineering teams to identify and deliver AI-driven capabilities that address real customer needs.
Stay up to date with emerging AI/ML technologies, frameworks, and best practices, and apply them where they create real impact.
Work across the stack, contributing to backend systems and data pipelines that support large-scale AI applications.
Troubleshoot and resolve complex system issues, including performance bottlenecks, race conditions, and memory-related challenges.
Approach problems with a strong analytical mindset, delivering robust solutions while contributing to a high-performing, collaborative team environment.

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.
Rapidly prototype 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.

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.
Rapidly prototype 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.

we are looking for an AI Researcher to help build the intelligence behind our AI security platform.
This is a hands-on research role focused on understanding how modern large language models and AI agents behave, identifying new attack vectors and protection techniques, and translating cutting-edge research into production-ready capabilities. The intelligence developed by this team is a core differentiator of our platform and a key driver of the company's success.
You will work at the intersection of machine learning, LLMs, and cybersecurity, partnering closely with AI engineers and product teams to develop technologies that directly power our product. We're looking for someone who enjoys understanding how neural networks and foundation models work, pushes the boundaries of AI research, and is excited to see their work deployed into production and used by customers.
What you will do
Research the behavior, capabilities, and limitations of modern large language models and AI agents.
Design novel techniques for detecting, evaluating, and proactively protecting against AI threats, prompt injection, model misuse, and emerging attack vectors.
Develop new approaches for securing AI systems and improving the intelligence that powers our platform.
Design and run experiments to evaluate model behavior, validate new ideas, and measure the effectiveness of protection techniques.
Build research prototypes and turn them into production-ready capabilities.
Work closely with Product and Engineering to translate research into scalable product features.
Stay current with advances in LLMs, foundation models, post-training techniques, AI security, and AI safety.
Contribute to the long-term technical direction of our company's AI security platform.

a rapidly growing startup company, developing the next-generation smart-infrastructure solution based on novel fiber-sensing technology (smart roads, smart cities, perimeters, and grid monitoring, etc.). The company offers an award-winning disruptive solution; a sensor free approach to smart infrastructure. The company is VC backed and in the revenues stage. Combining pioneering technology in optical fiber sensing with state-of-the-art Machine Learning, we help prevent environmental disasters, protect human lives, and keep critical energy and transportation backbones running smoothly. We are looking for a talented, self-driven, and hands-on DSP Researcher to join our Photonics R&D team. In this role, you will research and develop next-generation distributed fiber-optic sensing technologies, focusing on signal processing, system modeling, simulations, and experimental validation. Working at the intersection of physics, electro-optics, fiber-optic sensing, and DSP, you will transform complex physical phenomena into robust sensing solutions for real-world applications. You will tackle challenging physical and algorithmic problems, contribute to cutting-edge sensing products, and collaborate closely with multidisciplinary R&D teams. This role is ideal for someone who thrives in a fast-paced environment, enjoys working across disciplines, and is excited to take ideas from research and lab validation to large-scale deployment.
 
What Youll Do:
* Conduct experimental and theoretical R&D for next-generation distributed fiber-optic acoustic sensing systems.
* Develop, implement, and validate DSP algorithms for coherent optical sensing systems.
* Build end-to-end expertise across the full sensing pipeline, including optical signal generation and propagation, coherent detection, signal acquisition, DSP, and advanced data analysis.
* Design and run laboratory experiments to validate new concepts, improve system performance, and support current and future product generations.
* Develop simulations, models, and analysis tools using Python and/or C ++ for lab experiments, field data analysis, signal processing, and system -level performance evaluation.
* Work with field experiment data to identify performance gaps, validate models, and improve sensing capabilities.
* Collaborate with R&D teams across disciplines to develop, validate, and integrate new sensing capabilities.
* Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

1. AI Architecture & Technical Leadership

Guide AI architectural direction across platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.

2. Hands-on Applied Innovation (Core Pillar | ~50%)

Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:

De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering

3. Best Practices & Technical Enablement

Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)

Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.

We are seeking a highly accomplished AI Researcher to be part of the development of next-generation Foundation Models and Generative AI systems. In this role, you will bridge the gap between cutting-edge academic research and production-grade AI infrastructure. You will build, design, and fine-tune large-scale architectures (including LLMs, Multimodal, and Tabular Foundation Models) while applying them to complex, real-world domains like agentic behavior, coding and decision making.
In your day-to-day, you will:
Conduct pioneering research in deep learning and generative AI, specializing in Foundation Models, NLP, alignment, and multimodal learning
Deal with the impact of the models on production traffic, cost quality and latency
Train and scale state-of-the-art architectures using techniques like Post-Training SFT, Knowledge Distillation, LoRA, and sparse/hybrid model architectures
Own the AI lifecycle-from algorithmic prototyping and synthetic data generation to deploying production-grade AI features in fast-paced or big-data environments
Drive research initiatives, author publications/patents, and collaborate with other research teams to integrate intelligent capabilities into core products.

Required Senior AI Research Engineer
What Senior AI Research Engineers do:
Senior AI Research Engineers develop algorithmic solutions that power new innovative features and continuously improve existing ones, with a strong emphasis on training AI / ML models as a core part of the role. The work spans a wide range of domains - from training generative AI and LLM-based models to create musical content at scale, through building deep learning computer vision models that enhance user drawings, to developing real-time audio ML models for music transcription that elevate feedback.
You will take full end-to-end ownership of cutting-edge algorithms and AI models - leading the process from ideation and research, through development, to production-grade implementation and engineering within our products. This includes not only designing and building AI models, but also ensuring robust, efficient, and scalable integration into the app - directly shaping the experience of millions of users.

Req ID: 29153

As a Senior Machine Learning Scientist, you will work closely with engineers and product to design, develop, evaluate and deploy Gen AI powered solutions for scalable, customer-facing applications. Your work will focus on applying state-of-the-art agentic capabilities and driving business impact based on rigorous evaluations and experimentation.


Key Job Responsibilities and Duties:

Design end-to-end agentic systems, delivering high-quality, performant, and efficient solutions to production

Build agentic solutions for different tasks and use cases using state-of-the-art techniques

Develop and carry out evaluation strategies, including formulating new metrics and building evaluation judges

Pioneer and promote best practices and adoption of new technology in GenAI application development

Lead and mentor other team members, providing technical guidance and timely feedback to develop the team and motivate them to achieve their goals.

Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into ML solutions.

Conduct deep data analysis to evaluate model performance, label quality, features exploration.

Work closely with ML engineers to ensure and improve the solutions latency/throughput meets product requirements and ensure deployment of your model to production.

We are looking for a Staff Algorithm Engineer to join our core Algorithm team - a high-autonomy group responsible for the algorithm and ML systems at the heart of 4M's mapping engine. This is a role for engineers who think in systems, bring cutting-edge computer vision and algorithmic thinking to ambitious real-world challenges, and own problems end-to-end with an entrepreneurial drive.

In the AI era, being a strong engineer means more than writing great code. It means operating as both an architect and a team lead - designing the solution with clarity, then guiding AI agents to execute it at a level and speed that wasn't possible before. We are building a culture where this is the norm, and we're looking for someone who is excited to work and grow in that direction.

You will work across computer vision and algorithm disciplines - researching solutions, designing experiments, and delivering production-grade implementations - while collaborating closely with data engineering and product teams.





What You'll Do



Research and implement novel computer vision and algorithmic solutions for challenging real-world problems - spanning perception, learning, optimization, and graph-based reasoning.
Own algorithm quality end-to-end: design experiments, evaluate results, and drive iterations until production reliability targets are met.
Work across disciplines - sharing models, methods, and insights with algorithm, data engineering, and product teams.
Monitor production model health proactively; identify degradation early and lead remediation efforts.
Integrate AI tools into your workflow and grow into the role of architect and team lead - designing the solution, then directing agents to build it.
Raise the bar on the team's technical culture through code reviews, knowledge-sharing, and rigorous algorithmic thinking.