Mid–Senior Applied AI Research Engineer

10 hours ago

Tel Aviv, Tel Aviv, Israel SWAPP Full time ₪120,000 - ₪180,000 per year

We are teaching AI to understand "Space" (and it's really hard)

Role:

Mid–Senior Applied AI Research Engineer

Type:

Full-Time |
Location:

Tel Aviv (Hybrid)

Company:

SWAPP.AI

Most "Generative AI" generates pixels or text. We generate
Constructible Reality

. 

SWAPP.AI
is automating the architectural and engineering workflows end-to-end. We don't just make pretty pictures; our AI learns design languages and standards to generate precise, build-ready documentation, drawings, and models in record time.

The problem is massive:

Architecture is a graph problem, a geometry problem, and a constraint-satisfaction problem. It is also a semantic challenge—where unstructured data (NLP), building codes, guidelines, and design intent must be translated into rigorous spatial rules.

Who We Are Looking For

We are looking for a
Computer Scientist who specializes in AI

, not just an ML researcher.

  • You will thrive here if:

You get excited by algorithms, Graph Neural Networks, Computational Geometry, Graph Theory, multimodal reasoning, and turning "spaghetti research" into robust production APIs.
- You will likely not enjoy this role if:

You prefer to stay in Jupyter Notebooks and hand off code to "real engineers" to deploy.
- You will likely not enjoy this role if:

You view code purely as a prototyping tool rather than a production asset.

The Technical Challenge

You won't be just fine-tuning a model on clean data. You will be:

  1. Reasoning with Geometry:

Using Neural Networks and geometric deep learning to understand 2D/3D relationships and contexts.
2. Taming Multimodal Chaos:

Ingesting messy drawings, text, and BIM models to create unified, consistent representations.
3. Shipping to Production:

You own your stack—from the mathematical idea on the whiteboard to the CI/CD pipeline that deploys it.

The "CS Backbone" Requirement

We value strong CS fundamentals over knowledge of the latest flashy framework.

  • Must Have:

BSc/MSc in Computer Science (or equivalent). You know Big-O, data structures, and how systems behave in the real world.
- Must Have:

3+ years shipping ML to
production

(Industry experience).
- Must Have:

Strong Python engineering and programming skills (testing, typing, modular design, version control).
- The Stack:

PyTorch, GNNs, RL, Causal Inference, Vision/Geometry, and LLMs/NLP.

How to Apply

Send your CV to

.

If relevant, include a link to your GitHub and/or a specific example of a "hard engineering problem" you solved (e.g.,
"I reduced inference time by 50% by rewriting the custom kernel"

or
"I built a pipeline to parse messy unstructured data into strict JSON"

).

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