דרושים » תוכנה » Algorithm Developer

As part of the algorithm team for the next generation of autonomous driving, you will:
Responsibilities
Understand deeply, implement, train, and evaluate recent state-of-the-art algorithms in computer vision (e.g., object detection, semantic segmentation, self-supervised learning, vision transformers) for various domains.
Adapt algorithms into robust and scalable production-ready algorithms. Write clean and efficient code, ensuring compatibility with existing systems and frameworks, and real-time needs. Take full responsibility for your algorithms end-to-end until deployment on the edge device for production.
Develop and implement new computer vision algorithms (architectures, loss functions, post-processing, training, and evaluation methods) that surpass SOTA algorithms and achieve desired performance levels in our domain.

Backed by over 250 patents and trusted by global industry leaders including Toyota and BMW, we are redefining AI for the future of autonomous driving.
Our breakthrough Air2Road Localization technology fuses aerial imagery with real-time ground view data to achieve accurate vehicle localization, even in areas where GPS fails. Join our Air2Road team to shape the next generation of AI-driven localization, tackle cutting-edge research challenges, and turn state-of-the-art deep learning into real-world impact!
Responsibilities
As a senior member of the Air2Road algorithm team, you will:
Research, design, and implement state-of-the-art deep learning models in computer vision (e.g., detection, segmentation, transformers, self-supervised learning).
Use classical computer vision algorithms together with deep learning to build robust solutions.
Translate research into production-ready algorithms, writing clean, efficient, and scalable code in Pytorch.
Explore creative ideas, experiment with novel architectures, and continuously push beyond current SOTA.
Take ownership of your work end-to-end, from concept through prototyping to deployment in production.

You know that feeling when you get an LLM working perfectly in a playground, then realize you need to make it handle real money, real customers, and real uptime? That's where we live.

The GenAI team builds conversational experiences that feel human and decision engines that learn on their own. If moving from prototype to production with millions flowing through it gets you buzzing, keep reading.

What you'll do:

Design, build, and own end-to-end Generative-AI services from first prompt to production rollout.

Combine retrieval-augmented generation (RAG), function calling, and agents to automate underwriting, claims, and customer support flows.

Fine-tune open-source and commercial LLMs on proprietary datasets, evaluate with both offline benchmarks and online A/B tests.

Collaborate with product, data science, and design to invent new AI-first customer experiences (and kill the bad ones fast).

Build scalable APIs and micro-services (TypeScript/NestJS or Python/FastAPI) running in Kubernetes on AWS.

Instrument, monitor, and continuously improve model quality, latency, and cost you ship it, you own it

Mentor fellow engineers on GenAI best practices: prompt engineering, vector search, safety & guard-rails.

Contribute to internal tooling that automates the boring stuff (CI/CD, sandbox environments, branch deploys).