TomTom

Machine Learning Engineer

• Work directly with Perception Applied Scientists to enable highly efficient training and inference of object detection ML models and advise on frameworks for on-line use.
• Identify, design and implement core components to transition models from offline cloud processing to on-vehicle hardware (e.g., Nvidia Jetson), including model export (ONNX, TensorRT).
• Collaborate with TomTom’s Mobile Mapping group and embedded engineers to ensure smooth execution of perception models in vehicle.
• Drive technical decisions to improve engineering, testing, and operational excellence best practices.
• Develop resilient systems for processing and delivery of data.
• Lead projects within the team and across the organization to ensure successful outcomes.
• Support hiring and investments into team and product health.
• Participate in all phases of the project lifecycle: gathering requirements, designing, coding, testing, and integrating solutions.

Senior Machine Learning Engineer

Data Scientist

• Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how users interact with our products.
• Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
• Inform, influence, and support product decisions and deliveries.
• Product Roadmap; Help Product Management identify and optimize the decision-making process of identifying and classifying requirements/initiatives that have the biggest bang for buck. Help Product Management improve and optimize the impact of concurrent and competing requirements on the road map and existing commitments. Performing “what-if” analysis. Influencing product teams through data-driven recommendations. Spreading best practices to analytics and product teams. Evaluate investments and cost of opportunities
• Product Analytics; Monitoring key product metrics, and understanding root causes of changes in metrics. Building and analyzing dashboards and reports. Building key data sets powering operational and exploratory analysis. Evaluating and defining metrics
• Exploratory Analysis; Understanding ecosystems, user behaviors, and long-term trends. Identifying new points of leverage to influence key metrics. Building models of user behaviors

Associate Data Scientist

Full-stack Engineer

• Engineer the libraries, development and testing pipelines that directly support the running, measurement and management of algorithms developed by Road Features.
• Work directly with a talented Applied Science (AS) team to integrate Machine Learning (ML), Deep Learning (DL) and traditional algorithms into a common set of interfaces, regression testing and inference pipelines.
• Build highly efficient testing and release processes to ensure reliable, data driven algorithm releases.
• Collaborate and engage across the Organization to ensure algorithm libraries, once released, scale seamlessly in production.
• Drive the technical decisions to improve engineering, test, and operational excellence best practices.
• Develop resilient, scalable systems for the processing and delivery of data.
• Take charge of projects, both within your team and across the organization, to ensure successful outcomes.
• Support hiring for team vacancies, and investments into team and product health.
• Be involved in every phase of the project lifecycle, from gathering requirements to designing, coding, testing, and integrating solutions.

Senior Software Engineer, ADAS

IT Support

• What you'll do:
• Independently execute audits across the entire audit process to ensure the delivery of high-quality engagements, covering planning, execution, and reporting, while ensuring consistency and adhering to established procedures and standards
• Build and maintain strong partnerships with key stakeholders, including unit leaders, the Internal Controls team, and external parties
• Contribute to the development of the audit roadmap while supporting the overall strategy and procedures of the Internal Audit function
• Provide guidance and support to finance graduates and guest auditors as needed, facilitating their development and ensuring their effective contributions to the audit process
• Prepare comprehensive reports to be presented to Management, clearly communicating findings and actionable insights that are monitored and followed up on
• Participate and assist, from an Internal Auditor perspective, in high impact corporate projects

Internal Audit Manager

Product Manager

• Define and drive the vision, strategy, and roadmap for Orbis Product Create, ensuring alignment with Maps objectives and Living Maps Strategy
• Engage with Release Operations Managers, Expert Data Producers, and Map Consumers to understand requirements and translate them into product features
• Lead automation and standardization of product configuration, scheduling, and release processes to improve efficiency and predictability
• Collaborate with engineering managers, software engineers, and other product managers to deliver business value
• Own the change management process for product specifications and licensing, ensuring clear communication and documentation of changes and impacts
• Ensure map products comply with licensing standards (e.g., ODbL) and maintain high standards of quality, coverage, and data completeness
• Maintain visibility on market trends, competitor offerings, and customer feedback to inform product direction
• Coordinate with analytics, QA, Map Experts and platform teams to deliver a seamless product experience and support continuous improvement

Data Engineer

• Build the infrastructure and tooling required for optimal extraction, transformation, and loading of data from a wide variety of data sources using cloud-native big data services from AWS/Azure
• Deploy analytics tools that utilize the data pipeline to provide actionable insights into customer usage, operational efficiency and other analytical and business performance metrics
• Work with stakeholders including business analysts and data scientists to assist with data-related technical issues and support their data infrastructure needs
• Prepare data for modeling and analytics and enable effective data-driven decision making across stakeholders