Lead the evaluation and data-quality strategy for advanced AI vision and perception systems. Define metrics failure taxonomies and human-review protocols; translate evaluation findings into data strategy experiment priorities and product release decisions. Partner with model simulation and platform teams to drive production-readiness and continuous quality improvements.

What's the role?
We are hiring a Lead Data Scientist to own applied AI quality data strategy and downstream usefulness across advanced AI computer vision and perception systems. This person will define how we determine whether a system is working where it is failing what quality bar is required for release and how data evaluation and applied modeling should evolve to improve the product.
This is a senior role for someone who can bring rigor to ambiguous technical programs establish evaluation systems and translate model behavior into product decisions data strategy and concrete improvement loops.
What You Will Own
- 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
What You Will Do
- 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
Who are you?
What We Are Looking For
- 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
Education & Experience
- 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.
Nice To Have
- 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
The expected base salary range for this position is $160000 to $170000 per year. Actual compensation will be based on factors such as skills and experience. This position is also eligible for an annual performance bonus which is subject to company and individual performance.
Life at HERE comes with generous benefits to support your health and overall wellness. Benefits available to US-based HERE employees include health (Medical/Dental/Vision) insurance retirement savings plans paid time off & leave policies .
As part of HERE Technologies employment process candidates will be required to successfully complete a background verification process. Offers of employment and any related claims are subject to the successful completion of a background verification. Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring HERE will consider for employment qualified applicants with arrest and conviction records.
HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race color age gender identity sexual orientation marital status parental status religion sex national origin disability veteran status and other legally protected characteristics.
Under Section 503 of the Rehabilitation Act of 1973 and VEVRAA we have developed an affirmative action program (AAP) for individuals with disabilities and protected veterans. Portions of the AAP are available for review by applicants and employees through our People Team.
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Who are we?
HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes - from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely.
At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation provide opportunity and foster inclusion to improve people's lives. If you are inspired by an open world and driven to create positive change join us. Learn more about us on our YouTube Channel.