Pre-Sales Solutions Lead

1. Why This Role Exists

SpatialVerse is in a commercialization phase in North America that is shifting from existing key

accounts (KA) to down-market expansion. Our sales and marketing team is strong at commercial

execution and brand building ― but the key decision makers on the customer side are often

senior researchers: researchers in robotics, embodied AI, world models and spatial intelligence.

This role exists to communicate on the same wavelength as customer researchers and research

leads, exchange information at their level, and help Sales move opportunities to the next stage.

These key customer researchers do not care about commercial terms. They care about technical

approach, data quality and physical correctness, Sim2Real transfer efficiency and evaluation

protocols ― questions asked in the language of research. That channel mismatch leaves a large

share of opportunities stuck at an early stage: the sales conversation goes well, but the deal

does not move.

The core value of this role is to give SpatialVerse a face in North America that a researcher treats

as a peer ― using technical language they understand and trust to move opportunities into

demo / POC as quickly as possible, and ultimately to close the loop on the opportunity.

1. Core Responsibilities (by weight)

75%1. Pre-Sales & Opportunity Acceleration•

Partner with Account Executives to engage customer research teams directly (Research

Scientists, Tech Leads, CTOs and similar), covering technical discovery, solution design and

technical Q&A.

•

Own the full path from first technical contact to demo / POC: define demo scope and success

criteria, decompose data requirements, align delivery boundaries with internal Product and

R&D, and produce an executable POC plan.

•

Deliver product demos and technical walkthroughs on-site and remotely.

•

Author technical solution documents, technical Q&A material, and the technical sections of

proposals and review packages.

•

Build and maintain a network of relationships with technical decision makers across North

America.

25%2. Product & Frontier Intelligence

•

Continuously track the frontier in North America, especially Silicon Valley: latest papers and

open-source releases from research labs, competitor product moves and pricing, and shifts

in customer technical selection.

•

Distill this into internal, immediately consumable inputs ― weekly briefs, competitor

teardowns, opportunity maps ― that Product Managers use to set priorities and drive the

roadmap.

1. Qualifications

Must-have

•

Education: MS or above in artificial intelligence, computer vision, robotics, computer

graphics, machine learning, 3D vision or simulation; with tangible research output (papers,

open-source projects, datasets or patents). Participation in research published at top-tier

journals or academic conferences is a plus.

•

Understands the core problems, common methods and evaluation protocols in multimodal

large models, world models, embodied AI, robot learning and simulation; able to follow

technical detail.

•

3+ years in enterprise-facing technical pre-sales, solutions or technical support; or

equivalent R&D experience combined with deep customer collaboration.

•

Able to operate as a pre-sales professional: skilled at customer-facing communication, and

able to drive a POC through to project delivery ― discovery, solution design, resource

coordination, delivery and validation, end to end.•

Bilingual in Chinese and English (frequent collaboration with Product and R&D teams in

China; all customer-facing work in English).

•

Excellent two-way translation: turn technical value into customer business language, and

customer problems into executable internal requirements.

•

Self-driven; comfortable with North America time zones and travel; able to find a path in a

resource-constrained early-stage environment.

Nice-to-have

•

Industry experience in embodied AI, humanoid robotics, autonomous driving, XR or

industrial simulation; familiarity with NVIDIA Isaac Sim, Omniverse, MuJoCo, Unreal.

•

Familiarity with 3D data pipelines: point clouds, 3D Gaussian Splatting, OpenUSD, scene

graphs, annotation systems, format conversion.

•

0-to-1 enterprise selling experience in North America, or GTM experience on an early-stage

technical product.

•

Direct experience working with leading overseas research labs or robotics companies.

•

Hybrid experience as a Product Manager, DevRel or Research Engineer.