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 AI Algorithm Engineer - Vision Localization Group
Our vision Localization group is responsible for accurately localizing the vehicle on a high-definition 3D map with centimeter-level precision using surround camera systems to enable autonomous driving. Our work combines advanced geometric reasoning, scene understanding, and large-scale mapping to solve one of the core challenges of autonomous vehicles in complex real-world environments.
The role involves developing algorithmic and deep learning solutions that integrate mathematical optimization, computer vision, and 3D geometry. We work with modern neural network architectures including Transformers, GNNs, and CNNs to solve problems involving scene understanding, object association, and precise spatial reasoning in dynamic environments. The HD map contains rich geometric and semantic information that is critical for safe driving and cannot always be inferred reliably from images alone under all visibility conditions or viewpoints. In addition to achieving highly accurate localization, the team is also responsible for estimating map relevance and consistency with the current world state to ensure safe and reliable autonomous driving.
What will your job look like:
Develop state-of-the-art localization algorithms for autonomous driving using multi-camera surround vision systems.
Design and implement deep learning models based on Transformers, Graph Neural Networks, and Convolutional Neural Networks.
Solve challenging problems involving 3D geometry, scene understanding, object matching, and spatial reasoning.
Combine learning-based methods with classical optimization and geometric algorithms.
Own the entire lifecycle from prototyping to deployment.
Analyze real-world driving data and improve system robustness under diverse environmental and visibility conditions.
Drive innovative solutions for high-precision localization at production scale.

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 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.

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.

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.

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.