Full-Time
Principal Data Scientist
Gen AI and Vision
HERE Technologies
5,001-10,000 employees
PaaS for location-based solutions
Compensation Overview
$195k - $210k/yr
Remote in USA
Remote
Master's, PhD
 AI & Machine Learning (2) |
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 Data & Analytics (1) |
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- Deep experience in generative modeling for video, world models, diffusion models, multimodal systems, or adjacent advanced vision domains.
- Evidence of principal-level scope through technical leadership, research impact, architectural ownership, or shipped systems.
- Strong background in PyTorch and modern model training, fine-tuning, evaluation, and inference workflows.
- Experience adapting large pre-trained models to domain-specific use cases and hard production constraints.
- Good judgment on model quality, controllability, reliability, and deployment tradeoffs.
- Ability to work across research and engineering boundaries in a small, hands-on team.
- A Master's or PhD in Computer Science, artificial intelligence, machine learning, or a related field.
- At least 10 years of experience in deep learning, computer vision, or multimodal artificial intelligence.
- Own the model strategy and technical direction for advanced generative and multimodal vision systems.
- Set the research and engineering agenda for model adaptation, evaluation, and production readiness within this domain.
- Define how model inputs, controls, outputs, and interfaces are represented and integrated into downstream systems.
- Improve realism, controllability, temporal consistency, robustness, and deployment readiness over time.
- Work closely with evaluation, simulation, and platform engineers to define durable interfaces between research systems and production workflows.
- Drive model benchmarking, ablation studies, model-selection decisions, and the path from pre-trained baselines to production-ready capability.
- Raise the bar for technical quality, architecture, and execution within the model stack.
- Build and evolve end-to-end model workflows for complex vision and generative artificial intelligence systems.
- Identify and reduce failure modes such as structural drift, temporal instability, inconsistent outputs, and production fragility.
- Define the fine-tuning, adaptation, or hybrid-model strategy when pre-trained models do not meet product requirements out of the box.
- Partner with the evaluation lead to establish quality metrics, release gates, and production-readiness criteria.
- Help shape the roadmap from initial prototypes to scalable artificial intelligence capabilities across perception, generation, and related vision tasks.
- Contribute to deployment decisions around model packaging, inference optimization, and production performance tradeoffs.
- Mentor other scientists and act as the senior technical owner for the model domain.
- Experience with synthetic data, robotics, perception systems, geospatial artificial intelligence, autonomous systems, or advanced mapping products.
- Familiarity with conditioning mechanisms, structured control inputs, simulation-grounded models, or controllable generation.
- Experience running large-model inference, optimization, or fine-tuning on Amazon Web Services GPU infrastructure.
- Experience taking research models into production environments.
HERE Technologies provides a location-based Platform-as-a-Service (PaaS) for automotive, transportation, logistics, and enterprise customers. Its offerings are scalable, customizable location services that developers can integrate into apps and systems via APIs and SDKs, enabling features like maps, routing, geocoding, and traffic insights. The company differentiates itself through global reach, industry-focused solutions, and a flexible subscription/licensing model that supports custom deployments and integrations. Its goal is to help businesses build location-enabled applications and optimize operations by delivering reliable, adaptable location data and services at scale.
Company Size
5,001-10,000
Company Stage
Acquired
Total Funding
$19M
Headquarters
Eindhoven, Netherlands
Founded
1985
Get referred to HERE Technologies
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Simplify's Take
What believers are saying
- August 2026 Ryde and July 2026 JLR deals show demand for operationally critical location data.
- HERE's January 2026 Amazon collaboration expands into conversational in-vehicle navigation for automakers.
- AWS AI Competency and Esri's three-year agreement validate HERE's positioning in enterprise AI workflows.
What critics are saying
- Google Maps, Apple Maps, and TomTom compress pricing and push HERE toward commoditization.
- Automotive revenue concentration keeps HERE exposed if Hyundai or JLR insource mapping by 2027.
- HERE lacks consumer distribution; one OEM platform shift can erase years of enterprise wins.
What makes HERE Technologies unique
- HERE owns live map freshness for automakers like Hyundai, JLR, and Amazon in 2026.
- Its AI-powered routing stack fuses traffic, geocoding, EV charging, and dispatch reasoning.
- Esri and HERE deepen a 20-year partnership, embedding location data inside ArcGIS workflows.
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Benefits
Professional Development Budget
Flexible Work Hours
Growth & Insights and Company News
6 month growth
↑ 1%1 year growth
↑ 1%2 year growth
↑ 1%Ryde taps HERE to improve ride-hailing routes and ETAs in Singapore. Ryde is upgrading its routing and dispatch systems as Singapore's ride-hailing market grows more competitive and reliability becomes harder to win 12 Aug, 2026 In a city where a five-minute delay can be the difference between keeping or losing a customer, ride-hailing is often won in the invisible layer behind the app: maps, traffic data, dispatch logic and estimated arrival times. Singapore-based Ryde is now trying to improve that layer through a strategic partnership with HERE Technologies, the mapping and location data company. The two companies said in a joint statement that Ryde has integrated HERE Location Services into its platform to improve driver matching, routing accuracy and ETA predictions across Singapore. The deal is not about adding another button to Ryde's app. It is about making the core ride-hailing experience less uncertain: assigning the right driver, choosing a more realistic route, and telling riders more accurately when their car will arrive. For Ryde, which is listed on the NYSE American under the ticker RYDE, the partnership comes as competition in Singapore's mobility market remains intense. For HERE, it is another example of how location intelligence is becoming a key infrastructure layer for transport, logistics and quick commerce platforms in Southeast Asia. Why routing still matters in a small city. At first glance, Singapore may seem like a relatively easy market for routing technology. It is geographically compact, highly mapped and supported by strong public infrastructure. But the reality for ride-hailing operators is more complicated. Traffic conditions can shift quickly around expressways, Central Business Districts, schools, malls, industrial estates and housing towns. Roadworks, peak-hour congestion, rain and event-related traffic can all distort estimated arrival times. In ride-hailing, those distortions matter because the platform has to make decisions before the trip begins. If a system assigns a driver who appears close on the map but is separated by a difficult junction, a congested slip road or a slow-moving arterial route, the rider waits longer and the driver loses time. Multiply that across thousands of trips, and small mapping errors can become operational costs. Ryde said the integration of HERE's routing engine and real-time traffic intelligence is aimed at improving dispatch decisions, ETA predictions and navigation through changing road conditions. HERE's tools use live traffic data and route optimisation algorithms to support more accurate trip planning. "At Ryde, we're constantly investing in technologies that improve every journey for both riders and drivers," said Ryde CTO Nitin Dolli. "Our partnership with HERE strengthens the intelligence behind our platform, enabling more accurate routing, smarter driver allocation and better ETA predictions." The hidden economics of better ETAs. For riders, ETA accuracy is a convenience issue. For platforms and drivers, it is also an economic one. An inaccurate ETA can lead to cancellations, lower trust and poorer driver utilisation. If a driver is sent on a longer-than-expected pickup route, the time spent reaching the passenger is time not spent completing paid trips. If riders are repeatedly told that a vehicle is arriving sooner than it realistically can, they may switch to another platform. This is why ride-hailing companies invest heavily in what may look like routine back-end upgrades. Driver supply, demand forecasting, route calculation and pricing are all linked. Better routing can help platforms reduce idle time, improve matching and make the app feel more reliable without necessarily increasing the number of vehicles on the road. In Singapore, that is particularly important because the private-hire and taxi market operates within a tightly managed transport environment. Unlike some larger regional markets where platforms can scale supply more aggressively, Singapore's vehicle population is shaped by high ownership costs, regulatory controls and strong public transport alternatives. Platforms therefore have to compete not only on price and incentives, but also on reliability. HERE's Southeast Asia and India General Manager Abhijit Sengupta said ride-hailing platforms depend on accurate location intelligence to keep people and businesses moving. He added that the partnership with Ryde is meant to improve driver utilisation, reduce uncertainty and deliver a better end-user experience. Ryde's broader mobility play. Founded in Singapore in 2014, Ryde began with carpooling and has since expanded into private-hire rides, taxis and delivery. The company describes itself as a "super mobility app", although in practice it operates in a market where the dominant players have much broader ecosystems spanning payments, food delivery, advertising and financial services. One of Ryde's key differentiators has been its 0 per cent commission model for private-hire and taxi drivers. Instead of taking a cut from every completed ride in the way many ride-hailing platforms do, the company has sought to position itself as more driver-friendly. That strategy can help attract and retain supply, but it also means Ryde has to be disciplined about other parts of its business model, including technology costs, operational efficiency and customer retention. The HERE partnership fits into that context. A smaller ride-hailing player cannot always outspend larger rivals on subsidies or marketing. But it can compete by making its service more dependable in specific markets. In Singapore, where users often compare wait times across multiple apps before booking, even marginal gains in pickup accuracy can matter. The collaboration also reflects a wider shift in Southeast Asian mobility. Ride-hailing platforms are increasingly expected to support adjacent services such as parcel delivery, food delivery and quick commerce, all of which rely on precise location data. A routing engine that works well for passenger transport can also help in dispatching couriers or optimising delivery routes, although Ryde and HERE have framed the current announcement mainly around ride-hailing performance. A crowded field. Ryde's most obvious competitor in Singapore is Grab, the region's largest ride-hailing and delivery platform, which has deep consumer reach and a broad driver network. Gojek, owned by GoTo, also remains a major mobility brand in the city, though its regional footprint has been shaped by strategic pullbacks and market-by-market competition. Local and regional alternatives include TADA, which has promoted a zero-commission approach, as well as ComfortDelGro's CDG Zig app, backed by Singapore's largest taxi operator. Globally, the broader ride-hailing sector is shaped by companies such as Uber, Lyft, Didi and Bolt, though not all operate in Singapore. For Ryde, the challenge is not simply to match those companies feature by feature. It is to carve out a durable position in a market where scale, driver liquidity, trust and app reliability are closely intertwined. Location data as infrastructure. The partnership also says something about the role of mapping companies in the current phase of mobility. In the early years of ride-hailing, much of the public attention was on consumer adoption, driver recruitment and regulatory battles. Today, more of the competition is happening inside the routing stack. Maps are no longer static reference tools. They are live systems that feed into pricing, arrival estimates, fleet allocation and delivery promises. This is especially true in Southeast Asian cities, where congestion patterns can be uneven, informal pickup points are common, and road conditions can change quickly. Singapore is a comparatively orderly market, but it is also demanding. Consumers expect accuracy, regulators scrutinise transport operators closely, and competitors are only a tap away. In that environment, the quality of the underlying location data can shape the user experience as much as the app interface itself. For Ryde, integrating HERE's technology is unlikely to transform its market position overnight. But it addresses one of the most important questions in ride-hailing: can the platform make better decisions, faster, before the rider even gets into the car? If it can, the payoff may be felt not in a flashy new feature, but in something more valuable: fewer missed expectations. Editor, e27
HERE Technologies announced its HERE Road Alerts service now meets Data for Road Safety requirements to support Euro NCAP scoring. The service enables automakers to qualify for up to 1.35 Euro NCAP points through compliant hazard alert services. HERE Road Alerts delivers real-time information on hazards including accidents, roadworks, slippery roads and reduced visibility. The cloud-based service aggregates data from vehicle sensors, traffic feeds and other sources to provide timely warnings. The service helps automakers maximise Safety Assist scores whilst enhancing driver safety through earlier hazard awareness and safer speed adaptation. HERE can also support manufacturers in contributing vehicle-generated hazard data to the DFRS ecosystem, streamlining connected safety compliance and Euro NCAP eligibility.
HERE adds AI reasoning layer to route optimization - explains why orders go unassigned. New cognitive layer tells dispatchers why two trucks hit the same street or why orders sit unassigned - then suggests fixes a veteran dispatcher would make on instinct. Photo: Famartin (via source) HERE Technologies is moving a prototype AI reasoning layer into closed beta later this year that sits on top of its tour planning API and explains dispatch decisions instead of just handing them down. The layer tells a dispatcher why orders went unassigned, why two trucks are running the same street on the same day, and what constraints or driver skills caused the conflict - then suggests adjustments like loosening time windows, moving orders to the next day, or adding capacity. Why does route optimization need a reasoning layer? The perfect route plan built at 6 a.m. rarely survives contact with 9 a.m. traffic, a sick driver, or a carrier that goes dark. Bart Coppelmans of HERE Technologies said the gap between what dispatch plans in the morning and what a driver encounters in the field is the deeper problem his company wanted to solve. "If you have a perfect plan by six in the morning, by nine it can already be different because of unexpected events - a driver getting sick, a carrier going dark or last-minute order changes," Coppelmans said. "You need to be really dynamic and flexible, taking that into account." Where the underlying tour planning API tells a dispatcher what to do, the reasoning layer is meant to tell them why. "Why are these orders unassigned? Why are these two trucks going down the same street on the same day?" Coppelmans said. "It might be because of actual constraints, driving skills, or certain priorities." The layer doesn't stop at explanation. It's built to suggest fixes too, the kind of adjustments a veteran dispatcher makes on instinct. "Maybe loosen certain constraints, move some orders to tomorrow, or add two vehicles into the capacity," Coppelmans said. "That's the domain-specific reasoning layer." Coppelmans compared the shift to what's already happening in telematics, where fleets use generative AI to ask why a tire is losing pressure or why an asset went missing. Applied to dispatch, the same approach means a manager no longer has to intuit every downstream cause of a service failure. "It gives you proactive responses in terms of what you can do to further improve your plan and make it even better," Coppelmans said. Time-dependent optimization accounts for traffic changes throughout the day. HERE's tour planning engine has been in development for a decade, but new features are pushing adoption higher. Chief among those additions is time-dependent optimization that accounts for how traffic changes delivery capacity throughout the day. "At nine o'clock in the morning you can deliver fewer orders than at one o'clock in the afternoon because of traffic jams," Coppelmans said. HERE also added driver-friendly overlapping tours, which cut down on the territory conflicts drivers hate seeing on their routes, along with walk clustering - a feature that identifies when a driver should park once and deliver several stops on foot rather than repeatedly pulling in and out of a vehicle. "From one parking spot you can then deliver by walking to multiple different deliveries in a certain area, which might be more efficient than driving in and out of your vehicle," Coppelmans said. Last Meter Guidance collects sensor data from the field and feeds it back to dispatch. HERE's answer to the morning-versus-field gap is Last Meter Guidance, a client-side service that runs on a handheld device or driver app and collects sensor and positioning data from the field. "We're automatically collecting sensor and probe positioning points, we have our own positioning stack," Coppelmans said. "This service builds on top of that, really making sure we're learning from the field. We're collecting traces data from where the vehicle is parking, the walk path toward the building, flagging the building entrance and the final delivery end-point location." That data flows in both directions. Dispatchers get more accurate delivery windows, and drivers get parking and entrance guidance built on where previous drivers actually succeeded, not just where a map thinks a building's front door is. "There's no disconnect anymore," Coppelmans said. "Drivers are more comfortable trusting what is being planned and can say, 'Okay, this makes sense.'" For fleets running manual dispatch workflows, an AI-driven dispatch platform that removes rate-con entry and automates load tracking can cut process time by up to 95% compared to legacy TMS platforms that require manual data entry at every step - particularly when paired with ELD integrations that feed real-time positioning data back into the system. Location reasoning layer keeps LLMs from hallucinating geography. HERE paired the route optimization reasoning layer with a separate announcement: a location reasoning layer designed to keep large language models from making things up when asked about geography. Ask a generic LLM to find a restaurant halfway along a truck route, Coppelmans said, and the results are often unreliable. "If you now ask generic LLMs about a certain geo location, you get really random results, totally off, wrong geometry or wrong location," Coppelmans said. "You get a wrong POI that isn't nearby the river but somewhere else. You can get fooled easily, and these LLMs hallucinate based on geo-location queries." HERE Location Reasoning is meant to give agents the spatial grounding to answer those questions correctly, whether that means understanding where a vehicle sits on a road, drawing a boundary around a halfway point, or filtering points of interest that actually sit along the route. "That's the journey we're on, further supporting different agents being built in the market," Coppelmans said. "We're feeding them with a correspondent layer so they can really understand the context of location and ground it." Reasoning layer won't replace a carrier's own operational judgment. Coppelmans doesn't see the reasoning layer replacing a company's own operational judgment. Every carrier's KPIs and service-level agreements differ too much for one shared model to handle alone, he said. "You need to have your own agentic operations agent running, but feeding that with learnings from others is super crucial, otherwise you're siloed," Coppelmans said. The longer-term picture, he said, looks less like one company owning a single AI model and more like a network of agents querying each other - a carrier's dispatch agent checking in with a routing agent the way a person might ask a colleague for a second opinion. "You might think more in terms of agent-to-agent communications connecting certain things," Coppelmans said. "It doesn't necessarily have to be fully integrated into your own system, you can call different agents to pull other data sets to verify and qualify. But that's not something we're at yet, it's a little bit further down the road." What this means for dispatchers: The reasoning layer moves into closed beta later this year. If your fleet runs overlapping territories or struggles with unassigned orders that don't make sense on paper, the cognitive layer is built to surface the constraint or driver-skill mismatch causing the conflict - and suggest the fix a veteran dispatcher would make without being asked. Last Meter Guidance is available now for fleets that want driver field data feeding back into morning route plans.
HERE Technologies and Esri have signed a three-year agreement to jointly develop location-based analytics and visualization solutions supporting AI adoption. The collaboration combines HERE's mapping, traffic and mobility data with Esri's ArcGIS platform to make geospatial data more accessible to engineering teams and AI systems. The partnership aims to help customers across transportation, logistics, public sector, automotive and high tech sectors derive insights and improve decision-making. Built on ArcGIS, the new capabilities will support agentic workflows and reduce complexity in integrating location data at scale. The agreement deepens a 20-year partnership between the companies. HERE introduced its GIS Data Suite in 2025 as a foundational layer for the analytics capabilities being developed through this collaboration.
HERE Technologies and Esri partner to develop location analytics to support AI adoption. San Diego (Esri User Conference) 15 July 2026 HERE Technologies, the world's leading mapping and location data company, and Esri today announced a 3-year agreement to jointly develop location-based analytics and visualization solutions that support emerging AI use cases. The collaboration reflects growing demand from customers exploring AI applications and agentic workflows and seeking more effective ways to access, integrate and analyze large volumes of location data. By combining HERE's rich map content, traffic and mobility data with Esri's ArcGIS platform, the companies aim to make live and historical geospatial data more accessible to engineering teams and AI systems within analytics workflows. These capabilities will help customers across industries like transportation and logistics, public sector, automotive and high tech derive deeper insights and improve decision making. For more than 20 years, HERE and Esri have worked together to help organizations solve complex challenges with location data. This agreement deepens that collaboration and aims to help customers work with AI-ready geospatial analytics directly within existing ArcGIS environments, reducing the complexity of integrating and operationalizing location data at scale and supporting agentic workflows. "For over two decades, HERE has partnered with Esri to deliver trusted geospatial insights," said Chris Handley, Senior Vice President of Product Management at HERE Technologies. "As organizations explore new AI use cases, we can help them more easily access and analyze location data, enabling faster insights and more informed decisions." "Organizations are looking for analytics solutions that connect authoritative data, intuitive mapping, and scalable decision support," said Richard Cooke, Corporate Director of Global Business Development at Esri. "By bringing together HERE's trusted location data and the analytical power of ArcGIS, we will help customers extend what they can do within existing workflows and support emerging AI applications." By combining HERE's map, traffic and mobility data with ArcGIS, the partnership brings together authoritative location content with spatial analytics and visualization capabilities in a unified environment. The combined capabilities are intended to enable organizations to analyze real-world movement patterns and apply those insights to planning, operations, and decision making. HERE introduced HERE GIS Data Suite in 2025, providing a curated dataset designed for ArcGIS environments. The data suite serves as a foundational layer for the analytics capabilities developed through the agreement. HERE and Esri aim to help organizations move efficiently from geospatial data to analytics and real-world outcomes by combining trusted location data with scalable analytics tools. Media contacts Esri [email protected] HERE Technologies Danielle Beer [email protected] About Esri Esri, the global market leader in geographic information system (GIS) software, location intelligence, and mapping, helps customers unlock the full potential of data to improve operational and business results. Founded in 1969 in Redlands, California, USA, Esri software is deployed in hundreds of thousands of organizations globally, including Fortune 500 companies, government agencies, nonprofit institutions, and universities. Esri has regional offices, international distributors, and partners providing local support in over 100 countries on six continents. With its pioneering commitment to geospatial technology and analytics, Esri engineers the most innovative solutions that leverage a geographic approach to solving some of the world's most complex problems by placing them in the crucial context of location. Visit HERE at esri.com. About HERE Technologies HERE is the global leader in mapping and location technology. For more than 40 years, HERE has been powering innovation for the world's most recognizable companies: from launching its first digital map in 1985, to shaping the future of software-defined vehicles today. With the industry's freshest and richest unified map and a portfolio of products, services and solutions that serve the needs of multiple industries, HERE reveals opportunities that drive progress and unlock new possibilities for every moving vehicle. Discover more at here.com.