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we are on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners around the world, we are recognized as the leading transportation technology and service provider globally.
As a Staff ML Engineer at our company, you will play a central role in shaping how millions of riders and drivers move through our cities every day. Our team sits at the intersection of machine learning, optimization, and real-world operations - turning complex, multi-dimensional challenges into the real-time intelligence that powers our company's mass-scale automated dispatch system. This is a rare opportunity to work on problems that are genuinely hard, at a scale that is genuinely rare, where the solutions you build have a direct and visible impact on the efficiency and reliability of transit networks around the world.
About the Role:
Own the development of ML models and optimization algorithms that drive our company's real-time dispatch system - making smart, scalable decisions across thousands of simultaneous rides, drivers, and operational constraints.
Design and implement online algorithms for real-time decision-making, balancing system utilization with a consistently high quality of service for riders - where every millisecond and every percentage point of efficiency matters.
Model and mathematically represent competing demands on our company's system, translating messy real-world operational complexity into elegant, tractable formulations that can be solved at scale.
Use sophisticated statistical methods to analyse demand patterns, traffic dynamics, and fleet performance - generating insights that directly inform algorithm development and operational strategy.
Collaborate closely with engineering, product, and operations teams to bring complex algorithmic work to life in production - owning the full journey from research and prototyping through to real-world deployment and iteration.

As a research student , you will work on one of the teams core challenges in modern LLM-based systems, such as:

Agentic RAG
Advanced retrieval strategies, hybrid search, query rewriting, context optimization, and LLM-driven reasoning pipelines
Automatic Evaluation of Agents
LLM-as-a-Judge, scoring frameworks, hallucination detection, and robust evaluation methodologies
Agents for Knowledge Creation
Building agents that autonomously generate, refine, and maintain enterprise knowledge bases
Ontology-Grounded RAG
Enhancing models with domain-specific knowledge and structured representations
Data Analysis Agents
Agents capable of analyzing complex operational, product, and support data at scale
Fine-tuning LLMs for customer domain adaptation
Automatic agent improvement from user feedback including learning from errors, evaluations, and human signals
You will work one day per week, embedded directly in the Ask-AI research group, collaborating closely with senior researchers and engineers.

We are looking for a passionate VP of Engineering to help build our breakthrough AI product. As a VP of Engineering at Mosaic- AI, you will steer the development of our cutting-edge AI Sidekick and technologies.

In this pivotal role, your primary responsibility is to lead, guide, and mentor a team of talented software developers. You will be actively involved in planning, designing, and executing multiple software development projects while utilizing your extensive knowledge of software development to provide technical guidance and support to your team.



What are we looking for:

Strong Technical and Management Background
Expertise in Key Technologies:
Architecture savvy- A must
Proficiency in Python, with a solid understanding of software development best practices in this language- an advantage
Knowledge and hands-on experience with JavaScript, Typescript, and React/Angular- An advantage
Knowledge in Docker, micro-service architecture, FastAPI, Express, and Terraform- An advantage

This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety.

This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints.

What youll do
Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server).
Take models from research and turn them into production-ready, reliable components deployed on vessels.
Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing
Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination.
Make and justify tradeoffs between latency, accuracy, stability, and resource utilization.
Design and implement robust data and inference pipelines (video -> model -> actionable output for crew).
Develop benchmarking and evaluation workflows to measure performance end-to-end and support release gating.
Build and improve observability tools, including logging, monitoring, and debugging workflows for production systems.
Define and maintain clear interfaces between research code and production systems.
Work closely with research and backend teams to integrate new models into production systems.
Continuously improve system efficiency and reliability under hardware and runtime constraints.

We are seeking a Solution Engineer to join our Government Business Unit, based in Israel. In this high-impact role, you will bridge the gap between complex AI/data technologies and real-world intelligence operations. Working closely with the Sales team, you will serve as the technical authority during the pre-sales cycle for international and Israeli prospects, driving solution design, technical validation, and client engagement for defense and intelligence stakeholders.

The ideal candidate brings strong pre-sales experience, a deep technical background, and a proven background in intelligence or military operations (experience with the Israeli Navy or Defense/Intelligence agencies is a major advantage).

Key Responsibilities:
Lead the technical side of the sales cycle, translating complex customer needs into tailored, winning solution architectures.
Design, build, and deliver high-impact product demonstrations, technical trials, and Proof of Value (PoV) projects for key stakeholders.
Conduct discovery sessions to analyze client infrastructure, operational workflows, and domain-specific challenges.
Drive the technical responses for RFPs, RFIs, and complex defense tenders, working closely with internal R&D, Product, and Customer Success teams
Serve as a trusted advisor on Maritime Domain Awareness (MDA), API integrations, and hybrid SaaS deployments.
Provide client feedback and market requirements back to Product and R&D teams to shape the future of our platforms.

We are looking for an experienced MCP (Model Context Protocol) Software Engineer to design, develop, and optimize Model Context Protocol implementations. You'll work on building robust MCP servers, client integrations, and tools that allow AI systems to securely access and interact with various data sources and services.

What You'll Do:

MCP Development & Implementation
Design and develop MCP servers for various data sources (databases, APIs, file systems, cloud services).
Build and maintain MCP client integrations for AI applications and platforms.
Implement secure authentication and authorization mechanisms for MCP connections.
Develop custom MCP tools and resources to extend AI capabilities.

Architecture & Design
Architect scalable MCP solutions that handle high-volume data access patterns.
Design efficient protocol implementations that minimize latency and maximize throughput.
Create reusable MCP components and libraries for internal and external use.
Establish best practices for MCP server development and deployment.

Integration & Collaboration
Integrate to our identity platform.
Work with DevOps teams to deploy and monitor MCP services in production environments.
Partner with security teams to ensure MCP implementations meet compliance and security requirements.
Integrate MCP solutions with existing infrastructure and third-party services.

Quality & Performance
Write comprehensive tests for MCP implementations including unit, integration, and end-to-end tests.
Monitor and optimize MCP server performance and resource utilization.
Debug complex issues in distributed MCP environments.
Maintain detailed documentation for MCP servers and integration patterns.

Contribute to Open Source
Engage with the open-source community, contributing to the development and improvement of MCP.

Where You'll Be: Tel Aviv | Full-time, hybrid.

We're looking for a Tech Lead Engineer to drive the technical strategy for our cross-platform endpoint agent - built in C#/.NET and hardened for production across macOS, Windows, and Linux. You'll own features end to end across a managed fleet of enterprise devices, stay hands-on writing code, and raise the technical bar for a distributed engineering team. This role also means setting the standard for how the team uses AI coding agents responsibly - fast, but production-grade.

What Youll Do
Responsibilities:
Drive the technical strategy for our cross-platform endpoint agent, focusing on C#/.NET core logic while ensuring production readiness across macOS, Windows, and Linux.
Provide technical leadership to a distributed team of engineers, raising technical expertise and engineering practices across the organization.
Own features from discovery to delivery, solving complex domain problems across a managed fleet of enterprise devices.
Maintain a hands-on approach by writing code and mentoring engineers to elevate the organization's technical capabilities.
Architect the agent using C# and platform-specific extensions, ensuring performant integration with each operating system's security frameworks.
Own high-impact technical decisions that balance velocity, security, and reliability.
Deliver maintainable features supported by comprehensive testing, metrics, and monitoring.
Shape the agent roadmap and ensure resilient production systems in collaboration with cross-functional leadership.
Participate in design and code reviews to maintain high engineering standards.
Champion AI-assisted engineering across the team - set the bar for how coding agents accelerate delivery, and establish the practices and guardrails that keep output production-grade.

We're looking for a Senior Software Engineer to join our engineering team and take real ownership of features that deliver value at enterprise scale. In this role, you'll build security solutions for GenAI and Copilots, design scalable Big Data pipelines using cutting-edge technologies, and be part of a team that thinks creatively about complex problems and delivers real technological innovation.

This is a role for engineers who like to own things end-to-end from designing a solution to delivering value while working closely with the team through open discussions, design reviews, and code reviews.

What Youll Do
Responsibilities:
Assume ownership of features and deliver value to customers.
Design scalable Big Data pipelines using cutting-edge technologies.
Deliver high-quality engineering applying common engineering principals.
Work on building GenAI & Copilots security solutions.
Think creatively about complex problems and deliver technological Innovation.
Collaborate with others via open discussions, Design Reviews and Code Reviews.

We're looking for a Senior Applied AI Scientist to sit at the frontier of AI security - turning emerging threats into the detection models that protect how AI is used inside the world's largest organizations. You'll be part of the AI Security Research department, working hand-in-hand with security researchers to translate threat intelligence into trainable signals that catch malicious behavior and security risks across the AI-powered workflows of Fortune 500 companies.

You'll bring deep technical versatility - reaching for classical ML, deep learning, or agentic based approaches based on what the problem demands, and the evaluation rigor to know when a model is truly ready for the real world. If you want to define what AI security engineering looks like, not just practice it, this role is for you.

What Youll Do
Responsibilities:
Build, train, and ship detection models end-to-end, from raw data to production.
Choose the right method for each problem - traditional ML, deep learning, fine-tuned LLMs, agents or heuristics - based on theoretical insights turned into practical results.
Partner with security researchers to turn security research outputs and domain expertise into detection capabilities.
Own evaluation: design benchmarks, build labeled datasets, and define production standards.
Monitor models in production across all paradigms - ML, deep learning, LLM-based, and agentic systems to track degradation and ensure reliability
Iterate fast, with a tight feedback loop between model performance and product outcomes.

As a Senior AI Engineer on the Guardian Agents team, you will develop both our autonomous "digital employees" that execute security programs and the Control Plane that governs them. You will build a platform that allows customers to calibrate agents through conversation, ensuring human feedback is transformed into persistent organizational knowledge. By engineering these closed-loop systems, you enable agents to learn, evolve, and deliver accurate, goal-driven security outcomes at scale.

What Youll Do
Responsibilities:
Architect Autonomous Agents: Build goal-driven agents for complex security tasks like false-positive reduction and automated triage.
Build the Control Plane: Develop the infrastructure for Human-in-the-Loop (HITL) feedback, natural language calibration, and stateful memory systems.
Engineer for Growth: Implement evaluation frameworks and "organizational memory" to ensure agents stay accurate and follow historical security precedents.
Bridge AI & Engineering: Collaborate in a "Core Pod" with Security Researchers and Data Scientists to turn raw security signals into scalable, productized agent behaviors.
Scale Data Pipelines: Integrate agents with our Big Data foundation to ensure real-time context and tenant-safe execution.

The CTO Office is our core discovery engine, dedicated to navigating the rapid evolution in AI agent security and building the lighthouse. We are a high-agency team of ICs with integrated Engineering, Research, and Product mindsets. Our mission: incubate new ideas, define the approach to emerging attack classes, and build working POCs that prove technical reality. Guided by the CTO, Product, and GTM, we validate hard, open problems and actively support the Product organization by opening new development paths and seamlessly handing over advanced capabilities.

What Youll Do
Responsibilities:
Take a hard, open problem in AI agent security from this might be possible to a working POC that proves the company`s approach, grounded in technical reality.
Partner closely with Product, R&D, our Labs, and GTM. Dont just write about emerging problems. Think them through, design the solution, and POC it so customers see something real.
Own the end-to-end loop: scope the problem, build the prototype, evaluate it, document the approach, ship it.
Make the calls on architecture, tooling, and tradeoffs.
When a POC succeeds, own the handover to Engineering and Product. When a new direction needs its own team, lead the incubation.
Stay ahead of the rapid evolution in AI and proactively identify emerging trends.

Eitan Medical is an international Medical Device company that develops and manufactures innovative medical equipment. Specifically, we develop infusion pumps and their related accessory products. Job Description: Eitan medical is looking for a highly motivated Software QA Engineer with strong manual testing capabilities, hands-on automation experience, and practical usage of AI tools for software quality and testing activities. As part of the Digital Health Department, you will be responsible for designing, planning, and executing test scenarios for complex medical software systems. The role combines manual testing, automation development, backend/API validation, and AI-assisted QA workflows to ensure high-quality and reliable products used in real-life patient care. You will work closely with R&D, Product, and System Engineering teams in a dynamic and fast-growing environment. Direct Manager: Digital Health SW QA Team Leader

Alice’s Innovation team builds adversarial RL environments that train the world’s most advanced AI models to be safer. Our customers are the leading frontier AI labs, who use these environments for post-training reinforcement learning and safety evaluation. This is the bleeding edge of AI safety technology: the environments you build will directly shape how next-generation models learn to resist adversarial attacks. We’re looking for an AI Software Engineer to own the RL Gym platform end-to-end: from architecting multi-site web environments that simulate real-world attack surfaces, to optimizing our in-house orchestration harness (AgenticVerse) for high-performance delivery into customer training pipelines. This is a builder role. You’ll lead a small team (including a dedicated web environments engineer), operating with high autonomy, moving fast from concept to working prototype to production system. You’ll interact directly with customer engineering teams to understand their infrastructure constraints and deliver environments that meet their scale and reliability requirements. Why this role This is one of the few roles in the industry where your code directly influences how the next generation of AI models are trained. You’ll be at the center of advancing AI safety, building systems that the world’s top labs depend on to make their models more robust. The work is technically deep, the problem space is genuinely novel, and the field is moving faster than any team can keep up with alone. There’s no playbook. You’ll write it. What you’ll do: Platform & performance
* Own and evolve AgenticVerse, our in-house orchestration harness that provisions and manages RL environments at scale. Focus on performance: low-latency provisioning, high concurrency, minimal overhead per environment instance
* Design and build isolated, reproducible web environments using Firecracker microVMs or Docker containers
* Architect multi-site scenarios (3-4 interconnected web applications per task) with rich interactions: drag-and-drop, file uploads, authentication flows, LLM-in-the-loop components
* Implement deterministic verifiers that evaluate agent behavior with zero ambiguity Customer delivery
* Work directly with engineering teams at leading AI labs to integrate RL Gym environments into their training and evaluation pipelines
* Translate customer specs into working environments, iterating rapidly on feedback
* Own the technical relationship: SLAs, API contracts, integration architecture
* Adapt environment delivery formats to cus tomer infrastructure (real-time API calls vs. offline batch, managed vs. raw artifacts)
* Build customer-facing UIs when needed (dashboards, environment configuration portals, monitoring interfaces) Rapid prototyping
* Take ambiguous problem descriptions and produce working prototypes within days, not weeks
* Validate new environment types, interaction patterns, and verifier approaches quickly
* Build internal tooling that accelerates scenario authoring and testing

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. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!