Senior Context Fusion AI Engineer - Autonomous Vehicles
NVIDIA · Seattle, WA · 1 mo ago
EngineeringFull-time
We need to output HTML fragment with sections: headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections where there is real specific content. We must not repeat job title. No Job ID etc. Remove boilerplate. Preserve all substantive info.
We need to parse the posting.
Content:
Intro paragraph: "We are looking for a strong engineer to join the DRIVE Road Structure / Online Mapping / Context Fusion team. In this role, you will help craft and guide the future of our L3/L4 autonomous-driving solution by building a complete, learned 3D/4D world model that fuses navigation, ego-motion, perception, and sensor signals. You will work closely with perception, prediction, planning, and simulation teams to deliver a world representation that is complete, temporally consistent, uncertainty-aware, and robust enough to drive through the most challenging roads and intersections in L3/L4 autonomy level. This role is central to our vision for AV: developing a shared multimodal scene representation that can jointly support road understanding, 3D object and occupancy perception, motion prediction, and route-conditioned planning. Are you interested in inventing human-level AI for navigation in the unconstrained world under any conditions? If so, join us!"
That's about the role.
Then "What You'll Be Doing" list of responsibilities (multiple bullet-like sentences). We'll put under Responsibilities heading.
Then "What We Need To See" list of qualifications (education, experience). We'll put under Requirements or Qualifications.
Then "Ways To Stand Out From The Crowd" list of nice-to-have skills. Could be Skills.
Then there is salary info: "Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits."
Thus we have Pay and Benefits sections.
Also "Applications for this job will be accepted at least until September 22, 2026." That's schedule? Actually it's application deadline, not schedule. Could be Schedule? But schedule usually refers to work schedule (full-time, part-time). Not present. So we may not include Schedule.
We also have statements about NVIDIA being desirable employer, etc. That's fluff but maybe part of About the role? Could be omitted as boilerplate? It's not strictly boilerplate but it's promotional. Might keep in About the role? The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The NVIDIA fluff is not exactly those categories, but could be considered boilerplate? It's promotional. Might keep as part of About the role? However we should preserve substantive information. The fluff about NVIDIA being desirable employer is not substantive to the role; could be considered boilerplate. Safer to omit.
Also "#AutonomousVehicles #AutonomousVehicles" hashtags - remove.
Also "This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law." That's EEO boilerplate - remove.
Also ", , JR2025163" at end - remove.
Thus we need sections:
- About the role (maybe heading About the role) containing the intro paragraph.
- Responsibilities (What You'll Be Doing) with list items.
- Requirements (What We Need To See) with list items.
- Skills (Ways To Stand Out From The Crowd) with list items.
- Pay (salary range) with maybe paragraph.
- Benefits (equity and benefits) maybe combine with Pay? Could be separate Benefits section: "You will also be eligible for equity and benefits." That's benefits.
We could combine Pay and Benefits into one section? But instruction: prefer few substantive sections over many thin ones. However we have distinct Pay and Benefits content; we could make a Benefits section that includes both salary and equity. But they said include a section ONLY when posting has real, specific content for it. Pay is specific (salary range). Benefits is specific (equity and benefits). Could combine into a "Compensation and Benefits" section but headings list only Pay, Benefits. We could make a Benefits section that includes both salary and equity? Might be okay but they'd expect Pay heading for salary, Benefits heading for equity. However we could make a single "Compensation and Benefits" heading but not in allowed list. The instruction says use
for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections where there is real specific content. We must not repeat job title. No Job ID etc. Remove boilerplate. Preserve all substantive info.
We need to parse the posting.
Content:
Intro paragraph: "We are looking for a strong engineer to join the DRIVE Road Structure / Online Mapping / Context Fusion team. In this role, you will help craft and guide the future of our L3/L4 autonomous-driving solution by building a complete, learned 3D/4D world model that fuses navigation, ego-motion, perception, and sensor signals. You will work closely with perception, prediction, planning, and simulation teams to deliver a world representation that is complete, temporally consistent, uncertainty-aware, and robust enough to drive through the most challenging roads and intersections in L3/L4 autonomy level. This role is central to our vision for AV: developing a shared multimodal scene representation that can jointly support road understanding, 3D object and occupancy perception, motion prediction, and route-conditioned planning. Are you interested in inventing human-level AI for navigation in the unconstrained world under any conditions? If so, join us!"
That's about the role.
Then "What You'll Be Doing" list of responsibilities (multiple bullet-like sentences). We'll put under Responsibilities heading.
Then "What We Need To See" list of qualifications (education, experience). We'll put under Requirements or Qualifications.
Then "Ways To Stand Out From The Crowd" list of nice-to-have skills. Could be Skills.
Then there is salary info: "Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits."
Thus we have Pay and Benefits sections.
Also "Applications for this job will be accepted at least until September 22, 2026." That's schedule? Actually it's application deadline, not schedule. Could be Schedule? But schedule usually refers to work schedule (full-time, part-time). Not present. So we may not include Schedule.
We also have statements about NVIDIA being desirable employer, etc. That's fluff but maybe part of About the role? Could be omitted as boilerplate? It's not strictly boilerplate but it's promotional. Might keep in About the role? The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The NVIDIA fluff is not exactly those categories, but could be considered boilerplate? It's promotional. Might keep as part of About the role? However we should preserve substantive information. The fluff about NVIDIA being desirable employer is not substantive to the role; could be considered boilerplate. Safer to omit.
Also "#AutonomousVehicles #AutonomousVehicles" hashtags - remove.
Also "This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law." That's EEO boilerplate - remove.
Also ", , JR2025163" at end - remove.
Thus we need sections:
- About the role (maybe heading About the role) containing the intro paragraph.
- Responsibilities (What You'll Be Doing) with list items.
- Requirements (What We Need To See) with list items.
- Skills (Ways To Stand Out From The Crowd) with list items.
- Pay (salary range) with maybe paragraph.
- Benefits (equity and benefits) maybe combine with Pay? Could be separate Benefits section: "You will also be eligible for equity and benefits." That's benefits.
We could combine Pay and Benefits into one section? But instruction: prefer few substantive sections over many thin ones. However we have distinct Pay and Benefits content; we could make a Benefits section that includes both salary and equity. But they said include a section ONLY when posting has real, specific content for it. Pay is specific (salary range). Benefits is specific (equity and benefits). Could combine into a "Compensation and Benefits" section but headings list only Pay, Benefits. We could make a Benefits section that includes both salary and equity? Might be okay but they'd expect Pay heading for salary, Benefits heading for equity. However we could make a single "Compensation and Benefits" heading but not in allowed list. The instruction says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It gives examples but not strict enumeration; we could use other headings? Probably they expect those headings. Safer to use Pay and Benefits separate.
Thus:
About the role
About the role
...
Responsibilities
- ... ...
Requirements
- ... ...
Skills
- ... ...
Pay
...
Benefits
...
We must not include Schedule. Now extract content precisely. About the role paragraph: combine the intro sentences up to "If so, join us!" That's the motivational paragraph. Let's capture: "We are looking for a strong engineer to join the DRIVE Road Structure / Online Mapping / Context Fusion team. In this role, you will help craft and guide the future of our L3/L4 autonomous-driving solution by building a complete, learned 3D/4D world model that fuses navigation, ego-motion, perception, and sensor signals. You will work closely with perception, prediction, planning, and simulation teams to deliver a world representation that is complete, temporally consistent, uncertainty-aware, and robust enough to drive through the most challenging roads and intersections in L3/L4 autonomy level. This role is central to our vision for AV: developing a shared multimodal scene representation that can jointly support road understanding, 3D object and occupancy perception, motion prediction, and route-conditioned planning. Are you interested in inventing human-level AI for navigation in the unconstrained world under any conditions? If so, join us!" That's fine. Responsibilities: list each bullet from "What You'll Be Doing". The text after that heading includes multiple sentences separated by periods and semicolons. We need to split into list items. Let's extract: - Design and develop learning-based, multimodal sensor-fusion systems that transform synchronized sensor history, ego-motion, navigation context, and driving context into a unified spatiotemporal world representation. - Build architectures that jointly reason over camera, LiDAR, radar, and vehicle-state inputs, with appropriate handling of calibration, synchronization, coordinate transforms, sensor latency, and uncertainty. - Develop end-to-end and multi-task models that produce driving-relevant outputs from a shared scene representation, including; road graph elements such as lanes, boundaries, crosswalks, and traffic controls; semantic scene understanding; occupancy and free-space representations, including uncertain and occluded regions; - Develop scalable multimodal fusion architectures, including Transformer-based early, late, and hierarchical fusion; BEV, point/voxel, and image-based representations; temporal context aggregation; and cross-modal attention. - Create training, fine-tuning, and evaluation pipelines for large-scale multimodal datasets. Define multi-task objectives and metrics that balance perception quality, geometric consistency, prediction accuracy, latency, and safety-critical behavior. - Investigate foundation-model approaches for autonomous driving, including vision-language models, multimodal pre-training, representation learning, and efficient deployment of learned world models. - Work closely with perception, mapping, prediction, planning, simulation, data, and embedded-software teams to convert research advances into robust, production-quality AV systems. - Develop systematic analysis and debugging tools for model failures, cross-sensor disagreement, long-tail scenarios, distribution shift, and regressions in closed-loop simulation and on-road evaluation. Note there is a stray semicolon after "including;" but we keep as is. Now Requirements: "What We Need To See" list. Extract bullet points: - BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field, or equivalent experience. - 8+ years of experience, with at least 2+ years in the AV or robotics industry and 2+ years of leadership experience in a technically area (typo: "technically area" maybe "technical area"). - Strong experience developing production-quality sensor-fusion, perception, state-estimation, or autonomous-driving systems. - Demonstrated experience with learning-based multimodal perception or fusion involving two or more cameras, LiDAR, radar, map, navigation, and ego-motion signals. - Solid understanding of 3D geometry, coordinate frames, calibration, temporal synchronization, ego-motion compensation, tracking, uncertainty estimation, and sensor failure modes. - Experience with deep-learning methods for 3D perception, lego-context scene representation, occupancy/occlusion prediction, semantic segmentation, object detection/tracking, motion prediction, or planning. - Strong C++ and Python programming skills, with hands-on experience developing, training, and optimizing deep-learning models in PyTorch. Experience with CUDA, distributed training, mixed-precision techniques, and efficient GPU inference using NVIDIA software and hardware is highly valued. - Experience with Transformer, VLM, or multimodal foundation-model architectures, including pre-training, fine-tuning, distillation, quantization, or efficient inference. - Experience training and evaluating models at scale, including distributed training, dataset curation, offline evaluation, simulation-based validation, and production monitoring. - Ability to work across research and engineering boundaries: turn an ambiguous AV problem into measurable technical objectives, build the solution, and drive it to deployment. Note there is a duplicate line later about Transformer etc in Ways To Stand Out; we keep only once. Now Skills: "Ways To Stand Out From The Crowd" list. Extract: - Experience building multi-task driving models that jointly predict perception, road structure, occupancy, motion, and/or trajectories from shared multimodal features. - Experience with Transformer, VLM, or multimodal foundation-model architectures, including pre-training, fine-tuning, distillation, quantization, or efficient inference. - Experience with BEV, point-cloud/voxel, neural scene representation, 3D reconstruction, occupancy-flow, or spatiotemporal world-model methods. - Publications or open-source contributions in computer vision, robotics, machine learning, 3D perception, multimodal learning, or autonomous driving. - Experience optimizing models for automotive-grade real-time deployment using NVIDIA GPUs, TensorRT, CUDA, or edge inference toolchains. Note there is duplicate of Transformer etc; we keep. Now Pay: "Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5." We'll put that as a paragraph. Benefits: "You will also be eligible for equity and benefits." We'll put that as paragraph. Now ensure we don't include any boilerplate like "Applications for this job will be accepted at least until September 22, 2026." That's application instruction; remove. Also remove "This posting is for an existing vacancy." etc. Now produce HTML