דרושים » AI » AI Algorithm Engineer - Vision Localization Group

We are looking for an experienced Deep Learning Algorithm Developer to join one of our teams developing perception technologies for autonomous driving.
Our group tackles diverse challenges - from object detection and scene understanding to 3D perception - using large-scale, real-world in-house datasets and state-of-the-art deep learning models.
What will your job look like:
Develop and train neural networks for complex perception tasks in real-world driving environments.
Design and analyze deep learning pipelines, from data to deployment.
Collaborate with algorithm, software, and data experts to deliver production-ready models.
Research and apply new methods in computer vision, 3D perception, and multi-task learning to improve performance and efficiency.

Required Algorithm Researcher - Autonomous Driving (CTO Group)
The CTO Group is a small, elite team focused on the decision-making module of our autonomous driving system.
Our mission is to solve some of the hardest problems in autonomous driving by combining the full spectrum of modern computer science - from rigorous mathematical modeling, optimization, and algorithm design to deep learning.
The team develops the driving policies that translate system-wide inputs into safe, efficient, and human-like driving behavior. Our work spans classical algorithms, optimization under constraints, probabilistic reasoning, reinforcement & supervised learning, all grounded in real-world driving data.
The group is comprised of top researchers and developers and is led by world-class scientists, offering a unique opportunity to work closely with the CTO, shape the future of autonomous driving, and influence the company's technical direction.
What will your job look like:
Research and develop innovative algorithms for autonomous driving planning and decision-making.
Model complex real-world driving scenarios and formulate them as optimization, learning, or algorithmic problems.
Apply a broad range of techniques - from mathematical modeling and classical algorithms to machine learning and deep learning - to improve driving policies.
Analyze large-scale driving data to gain insights, validate hypotheses, and improve system robustness and performance.
Design and implement high-quality production-ready code in a research-driven environment.
Read, evaluate, and build upon state-of-the-art scientific literature in algorithms, AI, and machine learning.

Required Experienced Deep Learning Algorithm Developer - Perception Solutions
Join our Perception Solutions team, working on significant computer vision challenges and solving them with cutting-edge neural networks combined with heuristic solutions.
In this role, you will join at the beginning of an end-to-end development cycle, leveraging advanced approaches to enable direct vision modeling beyond traditional image-processing pipelines and help advance the next generation of autonomous driving technology.
What will your job look like:
Contribute to building a new deep learning project from scratch, with real impact on production systems.
Work on end-to-end model development, including problem formulation, data understanding, model design, training, evaluation, optimization, and deployment.
Develop and train state-of-the-art deep learning models for computer vision tasks.
Explore and define the best technical approach in an open, research-driven environment, where solutions are not predefined.
Tackle real-world challenges where model performance is critical and directly impacts product capabilities.

We are looking for a senior computer vision engineer: a hands on individual contributor whose work will be broad and touch many projects across the group, to lead long-term research initiatives and POCs that shape the technical direction of our technology.
What will your job look like:
Lead long-term applied research and POCs that determine the direction of our perception and autonomy technology.
Design and implement modern end-to-end perception and multi-modal learning systems across diverse vision tasks (e.g., detection and tracking, 3D reconstruction, multi-camera fusion, motion prediction).
Translate research innovations into high-quality, validated POCs designed for adoption by production teams and deployment within autonomous vehicle platforms.

We are looking for a Senior Algorithm Engineer to lead the design and development of large scale ML inference and data processing systems in production. In this role, you will work at the intersection of algorithms, data systems, and machine learning infrastructure, building scalable and efficient solutions that support high throughput model inference and large scale data processing. The position involves close collaboration with ML researchers and infrastructure teams to design robust systems that power production ML workloads.
What will your job look like:
Design and optimize algorithms and pipelines for large scale model inference
Build scalable systems for high throughput data processing and streaming
Develop data transformation and preprocessing components for ML workloads
Improve performance, efficiency, and reliability across distributed inference systems
Work closely with ML researchers, infrastructure, and platform teams
Drive architectural decisions for production ML and data systems.

The GNC Team Lead will oversee a small, high‑impact group responsible for developing and validating advanced Guidance, Navigation, and Control (GNC) algorithms within our companys defense‑technology product line. This role combines hands‑on technical expertise with early-stage leadership responsibilities, managing simulation specialists while driving innovation, system performance, and reliability.
The ideal candidate brings strong domain knowledge in GNC, autonomy, or aerospace systems, alongside proven ability, formal or informal, to guide and mentor technical staff in a fast‑paced startup environment.
Why Join us?
This is a unique opportunity to be at the heart of a defense-tech startup during its most exciting growth phase!
Responsibilities
Leading simulation engineers and providing technical direction, mentoring, and day‑to‑day guidance.
Developing and validating GNC algorithms, including guidance laws, navigation filters, and control loops.
Maintaining and improving high‑fidelity simulation environments that support robust modeling and system analysis.
Collaborating with software, hardware, and system engineering teams to integrate algorithms into the full system architecture.
Reviewing technical outputs, refining methodologies, and ensuring high-quality documentation and analysis.
Supporting field tests, analyzing performance data, and iterating on algorithms based on real-world results.
Identifying technical risks, opportunities, and long-term development needs within the GNC domain.

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!

Were looking for a Founding AI Engineer to build and define the research function at our company from zero. This is a rare opportunity to work on some of the hardest unsolved problems in applied AI and agents, with massive ownership, visibility, and room to grow into leadership quickly.
What Youll Do
Lead the AI domain at our company: Take ownership of our agent architecture and help define its next phases, standards, and direction.
Solve hard, unsolved problems: Work on challenges in AI agents, reasoning over complex systems, and autonomous decision-making that dont yet have clear playbooks.
Build production AI: Design, implement, evaluate, and deploy AI systems used by real customers.
Be outward-facing: Publish technical blogs, benchmarks, and papers; represent our company in the AI and data community.
Move fast with autonomy: Own problems end-to-end with minimal guidance, working directly with founders.
Deliver real customer value end-to-end: take features from idea to production, see them used by customers, and iterate based on real-world impact.

We are seeking a highly skilled and innovative Control Engineer to join our dynamic team dedicated to advancing the field of autonomous vehicles. As a Control Engineer, you will play a crucial role in designing, developing, implementing and testing hands on control algorithms to enhance the performance, safety, and efficiency of our autonomous vehicle systems.
please note that this position requires 2 days a week at our HQ in Jerusalem
What will your job look like?
Work on developing and optimizing control algorithms for the vehicle
Run and analyze simulations to test autonomous vehicle in virtual environments
Collaborate with hardware engineers to integrate control algorithms with the vehicle's hardware components, such as sensors, actuators, and onboard computers
Working with communication protocols and interfaces for both internal and external communications with different components of the system
Customer facing workshops to discuss and test your algorithms.
Testing your algorithms in an Autonomous vehicle.

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make our data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for our data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.