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We seek a strong, motivated, and highly technical researcher who can be part of the Innovation & Research team.

With an R&D mindset, the research outcome will be integrated into products.

The position allows gaining extensive knowledge about security-related issues based on Machine Learning algorithms that would help to secure organizational networks, including IoT devices.

You will be able to directly impact protections against major vulnerabilities.

Key Responsibilities
Be part of the Innovation team that is responsible for Policy Insights and IoT security solutions.
Build ML/AI solutions together with a strong partnership with our engineering team.
Work with data throughout the entire pipeline from Data Engineering and Data Analytics to ML/AI models.
Collaborate with all the data & research-related groups within .
Developing and implementing protection mechanisms against diverse cyberattacks, while investigating IoT devices to analyze their network behaviours and integration within complex systems.
Productization & development of technologies from the POC stage into an enterprise-scale security solution.
Work closely with other development teams, QA, product management, and customers.

We are looking for an experienced Senior Deep Learning Engineer with proven capabilities to lead the development of new products from concept to production. In this role, you will be a part of a highly talented team to drive inspection portfolio, while creating diverse Machine and Deep Learning algorithmic solutions.
A day in the life and how youll make an impact:
Design and Development of novel robust and efficient Machine Learning/ Deep Learning algorithms for major Vision challenges.
Create Proof of concept for new products and technology.
Evaluate and benchmark different algorithms on unique proprietary datasets.
Collaborate with team members to define future technology and features.

Our Algorithms team tackles the companys most pressing ML challenges, addressing real-world problems that have a direct impact on success. As part of this group of experienced, you will help establish a new research area within the company, uncovering insights and detecting anomalies that enhance the products overall performance.



What You'll Do:

End-to-end ownership: Identify and frame ambiguous business problems, set measurable success criteria, prototype solutions, and deliver production-ready algorithms.
Algorithm design: Develop and refine methods across clustering, graph learning, causal inference, time-series modeling, and optimization to enable new product capabilities.
Workflow deep dive: Work closely with Product teams to analyze current pipelines, map data and decision flows, and identify inefficiencies and opportunities for improvement.
Real-world data modeling: Explore, structure, and model construction-related data, including progress histories and schedules. Build robust datasets and meaningful features.
Collaborate with a dynamic team of talented researchers driving digital transformation in the construction industry.

Data-driven insights. Help identify new products and opportunities for the company in diverse domains.
Develop Machine Learning models. Define requirements & combine data from a wide set of sources to develop ML/DL models that will automate and speed up our business processes.
End to end model management. Conduct in depth research, POC, write production-grade code and implement it (all the way to production) using our MLOps Infra to solve a diversity of business problems

We are seeking a Senior Algorithm Engineer to join our core Algo team. This team is responsible for developing algorithms that address a wide range of Computer Vision/ML challenges in our effort to map the subsurface world.

Our algorithms leverage cutting-edge computer vision methodologies and extensive commercial Geographic Information System (GIS) datasets.

We are looking for a skilled Senior Algorithm Engineer with significant experience in building algorithm-based systems, especially in complex environments. You will design and implement end-to-end solutions from idea generation to production.

As an Algorithms Researcher , you'll join a team that explores the vast collection of relevant data and creates the optimization algorithms that drive Via's mass scale, complex, multi-dimensional automated dispatch.

What You'll Do:

Mathematically model the competing demands on Via's system.
Develop online algorithms for real-time decision-making, focusing on optimizing system utilization while maintaining a high quality of service for riders.
Design and implement highly efficient and scalable algorithmic solutions to power decision-making systems under large-scale, real-world operational demands.
Use sophisticated statistical methods to analyze demand, traffic and fleet performance, and generate insights that inform algorithm development.

Required Senior Deep Learning Algorithm Researcher - Air2Road Localization
Description
Backed by over 250 patents and trusted by global industry leaders including Toyota and BMW, we are redefining AI for the future of autonomous driving.
Our breakthrough Air2Road Localization technology fuses aerial imagery with real-time ground view data to achieve accurate vehicle localization, even in areas where GPS fails. Join our Air2Road team to shape the next generation of AI-driven localization, tackle cutting-edge research challenges, and turn state-of-the-art deep learning into real-world impact!
Responsibilities
As a senior member of the Air2Road algorithm team, you will:
Research, design, and implement state-of-the-art deep learning models in computer vision (e.g., detection, segmentation, transformers, self-supervised learning).
Use classical computer vision algorithms together with deep learning to build robust solutions.
Translate research into production-ready algorithms, writing clean, efficient, and scalable code in Pytorch.
Explore creative ideas, experiment with novel architectures, and continuously push beyond current SOTA.
Take ownership of your work end-to-end, from concept through prototyping to deployment in production.

Requied Deep Learning Algorithm Developer - ADAS group
Description
As part of the algorithm team for the next generation of autonomous driving, you will:
Responsibilities
Understand deeply, implement, train, and evaluate recent state-of-the-art algorithms in computer vision (e.g., object detection, semantic segmentation, self-supervised learning, vision transformers) for various domains.
Adapt algorithms into robust and scalable production-ready algorithms. Write clean and efficient code, ensuring compatibility with existing systems and frameworks, and real-time needs. Take full responsibility for your algorithms end-to-end until deployment on the edge device for production.
Develop and implement new computer vision algorithms (architectures, loss functions, post-processing, training, and evaluation methods) that surpass SOTA algorithms and achieve desired performance levels in our domain.

We are looking for a Machine Learning Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability.

As a Tech Lead on the ML team , you will focus on designing and maintaining the core infrastructure that empowers the Machine Learning Engineers working within Data Science product teams. Youll collaborate closely with stakeholders across data science, product, and engineering, playing a pivotal role in driving the business by architecting and enabling the infrastructure for machine learning model development, serving, and lifecycle managementthe foundation of our product.

Responsibilities:

Partner with MLEs in Data Science product teams and key stakeholders to design and maintain infrastructure for:
Data wrangling supporting and enabling data requirements for research, training, validation, and testing.
End-to-end ML delivery enabling model performance development, training, validation, testing, and version control.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.
Build and support monitoring and observability tools dashboards, alerts, and performance tracking of models in production.
Lead architecture projects such as:
Feature Store centralizing feature engineering and serving across teams.
Vector Databases enabling large-scale embedding storage and retrieval for advanced ML applications.
GPU Cluster Scaling optimizing distributed training and inference infrastructure.
Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.