Note: The job is a remote job and is open to candidates in USA. HERE Technologies is a location data and technology platform company. They are hiring a Lead Data Scientist to own applied AI quality, data strategy, and downstream usefulness across advanced AI, computer vision, and perception systems.
Responsibilities
- Own the evaluation framework and quality strategy for advanced AI and vision systems
- Define pass/fail metrics for output quality, structural fidelity, temporal consistency, label quality, robustness, and operational repeatability
- Own data and validation strategy for improving model quality and downstream usefulness
- Lead artifact auditing, failure taxonomy development, release-quality reporting, and evidence-based prioritization
- Measure whether outputs are suitable for perception, mapping, generative AI, and customer-facing use cases
- Partner with model, simulation, and platform owners to drive quality improvements and production-readiness decisions
- Build and evolve metric suites for output quality, fidelity, repeatability, and downstream usefulness
- Define human-review protocols and product acceptance thresholds for complex AI systems
- Evaluate whether outputs preserve the structure, semantics, and consistency expected by downstream applications
- Translate evaluation findings into data strategy, experiment priorities, and applied modeling opportunities
- Help define dataset design, validation slices, and quality-improvement loops across the product
- Create experiment and release reports that turn technical output into clear product decisions
- Help prioritize what the team should fix next based on evidence rather than intuition
- Establish evaluation foundations that remain useful across future AI, perception, and mapping capabilities
Skills
- Strong background in applied machine learning, computer vision, synthetic-data evaluation, or perception-system validation
- Experience designing metrics and evaluation frameworks for generative, simulation, or perception systems
- Experience connecting model behavior, data quality, and product outcomes in ambiguous AI systems
- Ability to translate research-quality experiments into practical engineering and release decisions
- Strong analytical judgment and clear written communication
- Comfort owning both strategy and execution in a small team
- Master's or PhD in Computer Science, AI, Machine Learning, or related field
- 5-8 years of experience in deep learning, computer vision, or multimodal AI
- Experience with simulation, autonomous systems, geospatial AI, or map-grounded perception tasks
- Familiarity with video quality metrics, structural similarity measures, temporal consistency checks, segmentation and detection evaluation, or label-quality assessment
- Experience assessing synthetic-to-real transfer, dataset usefulness for downstream models, data curation strategy, or production quality governance
Benefits
- Annual performance bonus, which is subject to company and individual performance
- Health (Medical/Dental/Vision) insurance
- Retirement savings plans
- Paid time off & leave policies
Company Overview
Company H1B Sponsorship