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We are looking for a highly motivated and resourceful Lawyer / LL.B graduate to join our company for the next phase of our fast-moving story as a Legal Operations Manager.

Responsibilities:
High scale management of small claim cases in different US states & courts, including case submissions, pleads writing & filing, case tracking, and serving.
Identifying and resolving case errors.
Managing our communications with court clerks.
Research of different courts procedural demands and small claims processes.
Legal processes optimization & automation High scale management of small claim cases.

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at our company.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

we are a global leader in autonomous vehicle (AV) technology, pioneering advanced driver-assistance systems (ADAS) and self-driving solutions.
Across the company, Senior Deep Learning Algorithm Developers work at the forefront of AV/ADAS innovation - designing, training, and optimizing deep neural networks for tasks such as perception, mapping, and scene understanding. This includes working with large-scale datasets, leveraging frameworks like PyTorch or TensorFlow, and applying state-of-the-art techniques to tackle complex perception and decision-making challenges in real-world driving scenarios.
At our company, Senior Deep Learning Algorithm Developers contribute across multiple AI domains, with most opportunities in Computer Vision and additional roles in areas such as NLP/LLMs and 3D Perception (Radar, LiDAR, Fusion). This role serves as a central entry point, enabling us to align your expertise and aspirations with the projects and teams where you can make the greatest impact.
What will your job look like?
Design, develop and implement deep learning algorithms to solve complex problems in computer vision
Take ownership of deep learning projects: Compose product requirements, design solutions, oversee execution, and collaborate with talented Algorithm Developers.
Collaborate with cross-functional teams to understand requirements and develop solutions.
Analyze large datasets to improve algorithm performance and robustness.
Research the latest advancements in deep learning, multi-task learning, AI architectures, and apply them to enhance our algorithms.

we are a global leader in autonomous vehicle (AV) technology, pioneering advanced driver-assistance systems (ADAS) and self-driving solutions.
Across the company, Senior Deep Learning Algorithm Developers work at the forefront of AV/ADAS innovation - designing, training, and optimizing deep neural networks for tasks such as perception, mapping, and scene understanding. This includes working with large-scale datasets, leveraging frameworks like PyTorch or TensorFlow, and applying state-of-the-art techniques to tackle complex perception and decision-making challenges in real-world driving scenarios.
At our company, Senior Deep Learning Algorithm Developers contribute across multiple AI domains, with most opportunities in Computer Vision and additional roles in areas such as NLP/LLMs and 3D Perception (Radar, LiDAR, Fusion). This role serves as a central entry point, enabling us to align your expertise and aspirations with the projects and teams where you can make the greatest impact.
What will your job look like?
Design, develop and implement deep learning algorithms to solve complex problems in computer vision
Take ownership of deep learning projects: Compose product requirements, design solutions, oversee execution, and collaborate with talented Algorithm Developers.
Collaborate with cross-functional teams to understand requirements and develop solutions.
Analyze large datasets to improve algorithm performance and robustness.
Research the latest advancements in deep learning, multi-task learning, AI architectures, and apply them to enhance our algorithms.

We are looking for a highly motivated and experienced Head of Customer Acquisition to join our company for the next phase of our fast-moving story.

Responsibilities:
Support global marketing organizations, build and manage our marketing strategy and plans to optimize business goals.
Build Go-To-Market strategies of new product features and execute them with your team.
Developing tactics and playbooks across different marketing channels (CRM, partnership, social, etc.).
Understand users and their feedback, conduct market research, and ensure ongoing product market fit.
Defining marketing targets, forecasting, brand strategy and long-term planning.
Work closely alongside developers, designers, data analysts and product team to drive business growth and value creation.

we are a pioneering force in the autonomous vehicles (AV) industry.
Join us to build the brain behind the car - a large-scale, multi-task neural network that powers the core of our companys autonomous stack.
Youll design and train cutting-edge deep learning models tailored for our custom EyeQ chip, tackling end-to-end challenges and deploying real-world solutions.
From novel architectures and advanced training techniques to performance tuning under tight constraints, youll work closely with software and hardware teams to turn research into high-impact, production-ready systems.
If youre a brilliant, hands-on researcher with a passion for shaping the future - this is your launchpad.
Our team is at the forefront of our companys most advanced AI efforts. As a central hub for deep learning innovation, were trusted with designing the core neural network architecture that powers the companys flagship products. If youre seeking a high-impact role among top-tier researchers and developers - this is the place to be.

our company's EyeQ Platform Group (EPG) is seeking a motivated Formal Verification Engineer to join our team and contribute to development of hardware verification environments.
This position offers an opportunity to apply formal methods to verify the correctness of various complex digital systems.
This is an exciting opportunity to join a team of talented engineers, working cutting edge technologies in the field of autonomous vehicle.
What will your job look like:
Be the owner of formal verification environment from first draft to sign-off stage
Apply formal methods to verify the correctness of various complex digital systems
Work with HW architects\designers to define assumptions, rules and cover properties
Help define the formal verification methodology and environment to be applied by the team
Explore new Formal methods and Tools
Work with tools like Cadence JasperGold, Verisium manager, Xcelium, Indago
Analyze verification results, identify bugs, and collaborate with engineers to resolve design issues
Develop generic formal blocks\functions of commonly used logic, to be later used off the shelf.

We are our company's Production Test team - responsible for the definition, development, and deployment of production test operations for the worlds most advanced SoCs for ADAS and self-driving vehicles.
This is your opportunity to join a team during its initial forming stage and leave your mark as our company assumes full ownership for its silicon production operations to enable high volume manufacturing for cutting-edge automotive products.
What will your job look like?
Work closely with the design teams from early stages of the design process to review DFX architecture and define test requirements.
Define test methodologies and generate test content for high-speed interfaces of embedded IP blocks (LPDDR4/5, PCIe Gen4/5, D/C/MPHY).
Test program coding, pattern conversion and pre-Si validation (virtual test simulations)
Support Load Board and Probe Card design activities.
Lead post-Si test program debug activities to enable delivery of samples to internal and external customers.
Test program characterization and tuning to enhance test program quality to meet automotive standards.
Support Quality & Reliability team to enable effective and timely qual plan execution.
Lead test deployment activities with tier-one Foundry and OSAT vendors to enable large-scale Wafer-Sort and Final-Test operations.

We are looking for a highly motivated and experienced Marketing Analyst Position to join our company for the next phase of our fast-moving story.

Responsibilities:

Design and monitor ongoing marketing data to drive key business decisions.

Analyze large and complex data sets to discover product insights and help translate them into actionable recommendations.

Translate business questions and requirements to structured analysis.

See beyond numbers and help influence and support our business decisions.

Locate gaps and opportunities in campaigns performance and budget management.

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at our company.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at our company.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

We are looking for a Senior PCB Design layout Engineer to join our Hardware engineering team at the Autonomous Vehicle Platform department as a key player in the development of next-generation ECU (electrical control unit) for autonomous vehicles.
What will your job look like?
Working closely with hardware and mechanical design engineers, you'll perform PCB layout our company's ECUs and other products.
Complete development of CAD layout from footprint definition, detailed component placement, constraints management, with a concept of topology and signal and power integrity.
Be responsible for the design releases required generation of artwork files, ODB++, FAB drawings, ICT report, and electronic PCB documentation.
Your designs will need to follow IPC class 3 , signal and power integrity constraints, EMI/RFI control and automotive regulations.

We are looking for a Senior PCB Design layout Engineer to join our Hardware engineering team at the Autonomous Vehicle Platform department as a key player in the development of next-generation ECU (electrical control unit) for autonomous vehicles.
What will your job look like?
Working closely with hardware and mechanical design engineers, you'll perform PCB layout our company's ECUs and other products.
Complete development of CAD layout from footprint definition, detailed component placement, constraints management, with a concept of topology and signal and power integrity.
Be responsible for the design releases required generation of artwork files, ODB++, FAB drawings, ICT report, and electronic PCB documentation.
Your designs will need to follow IPC class 3 , signal and power integrity constraints, EMI/RFI control and automotive regulations.

You will be part of our company's REM department, which is responsible for the automatic High-Definition map-making process, a key technology in our autonomous driving and advanced driver-assistance systems.
This process involves running advanced algorithmic code in a massively parallel way, utilizing Big Data technologies, and managing a complex system that requires both technical depth and strategic thinking.
We are seeking a Backend & Data Engineer to join our Innovation Team within our Mapping Division. This role is best suited for engineers with strong system-level thinking, a can-do approach, and a hands-on mindset, with the ability to design, build, and optimize complex systems operating at scale.
What your job will look like:
Develop and maintain backend and data-processing components in large-scale systems
Design, implement, and optimize data pipelines and distributed processing flows
Work with large-scale storage systems (e.g., S3) and high-volume data access patterns
Optimize systems and code across multiple layers - from architecture to implementation
Identify performance bottlenecks, debug complex issues, and drive root-cause solutions
Work across teams and domains, reading, improving, and refactoring existing code
Take part in technical design and decision-making, balancing performance, scalability, and maintainability.

You will be part of our company's REM department, which is responsible for the automatic High-Definition map-making process, a key technology in our autonomous driving and advanced driver-assistance systems.
This process involves running advanced algorithmic code in a massively parallel way, utilizing Big Data technologies, and managing a complex system that requires both technical depth and strategic thinking.
We are seeking a Backend & infrastructure engineer to join our Innovation Team within our Mapping Division. This role is best suited for engineers with strong system-level thinking, a can-do approach, and a hands-on mindset, with the ability to design, build, and optimize complex systems operating at scale.
What your job will look like:
Develop and maintain backend and data-processing components in large-scale systems
Design, implement, and optimize data pipelines and distributed processing flows
Work with large-scale storage systems (e.g., S3) and high-volume data access patterns
Optimize systems and code across multiple layers - from architecture to implementation
Identify performance bottlenecks, debug complex issues, and drive root-cause solutions
Work across teams and domains, reading, improving, and refactoring existing code
Take part in technical design and decision-making, balancing performance, scalability, and maintainability.