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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.

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.

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.