דרושים » תוכנה » Senior Software Engineer - Data Path

we are looking for a Senior Software Engineer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless workers who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
Work in a team of top-of-the-line software engineers, developing state-of-the-art company AI OS platform for deployment in the Cloud to serve mission-critical enterprise-level data.
our company on Cloud software design includes:
A highly scalable distributed platform featuring complex high-availability mechanisms, and advanced APIs, interoperable with a diverse software ecosystem.
Deploying our company OS in all major hyper-scalers cloud vendors.

As an ML Software Engineer with a focus on low-level and CUDA-based optimizations, you will play a key role in shaping the design, performance, and scalability of machine learning inference systems. Youll work on deeply technical challenges at the intersection of GPU acceleration, systems architecture, and ML deployment.
Your expertise in CUDA, C/C++, and performance tuning will be crucial in enhancing runtime efficiency across heterogeneous computing environments. Youll collaborate with designers, researchers, and backend engineers to build production-grade ML pipelines that are optimized for latency, throughput, and memory use, contributing directly to the infrastructure powering next-generation AI products.This role is ideal for an engineer with strong systems-level thinking, deep familiarity with GPU internals, and a passion for pushing the boundaries of performance and efficiency in machine learning infrastructure.

Responsibilities
Design and implement highly optimized GPU-accelerated ML inference systems using CUDA and low-level parallelism techniques
Optimize memory, compute, and data flow to meet real-time or high-throughput constraints
Improve the performance, reliability, and observability of our inference backend across diverse compute targets (CPU/GPU)
Collaborate with cross-functional teams (including researchers, developers, and designers) to deliver efficient and scalable inference solutions
Contribute to ComfyUI and internal infrastructure to improve the usability and performance of model execution flows
Investigate performance bottlenecks at all levels of the stack-from Python to kernel-level execution
Navigate and enhance a large, complex, production-grade codebase
Drive innovation in low-level system design to support future ML workloads

We are looking for an experienced and highly motivated excellent Software Engineer to join the Haifa Image Generation group. Youll design and develop software for the next generation CT product, implementing new complex image processing algorithms and control logic enabling new premium CT products that are expected to revolutionize the industry. You should have a strong C++ background, good communication skills, and an ability to integrate well as part of the team and global organization, motivated to solve sophisticated problems. Youll be developing CT reconstruction software applications and services computational tools, working in the areas of algorithm development, control logic, platform, application, AI, collaborating with engineers across the globe from US, Sweden, Japan, India and China. Experience in developing software for healthcare and especially for CT is a strong advantage.
Job Description
Roles and Responsibilities
In this role, you will:
Build, design and implement CT image generation/reconstruction software - algorithms and applications.
Lead complex SW designs and related discussions
Collaborate with system engineers, algorithm developers and other software developers from across the globe to implement solutions that are aligned with and extend shared platforms and solutions for CT
Apply principles of SDLC and methodologies like Agile/Scrum, CI, requirements analysis, documentation practices, software and product security, scalability, refactoring and testing techniques
Understand, assess and optimize algorithms and applications performance
Take part in developing a common imaging platform for all imaging products
Work on core data structures and algorithms and implement them using C++, Python, CUDA, OpenCL.

You are a Senior AI Software Engineer looking to join a GenAI Infrastructure team and build production-grade GenAI capabilities and the infrastructure behind them. You will be a hands-on engineer focused on AI agents, RAG pipelines, tool-calling workflows, backend services, data access layers, evaluation, observability, and reusable GenAI infrastructure used across product teams. You will not be focused solely on model research or prompt design. Instead, you will be a strong software engineer who can design, build, ship, and operate reliable AI-powered systems in production.
A Day In Your Life
Build reusable infrastructure, SDKs, and internal frameworks for AI-powered product capabilities.
Design and implement AI agents, RAG flows, tool-calling workflows, and LLM orchestration pipelines.
Build production-grade GenAI services, APIs, and backend infrastructure.
Integrate LLM workflows with internal microservices, data platforms, vector search, and event-driven systems.
Design secure data-access patterns that enforce authorization, tenant separation, and user-level scope.
Implement evaluation, tracing, monitoring, and quality-control mechanisms for GenAI systems.
Improve latency, reliability, fallback behavior, cost efficiency, and production readiness.
Work on customer-facing AI experiences, including conversational and proactive agentic product flows.
Collaborate with backend engineers, product managers, data engineers, AI/ML engineers, and domain experts.