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We are looking for an experienced hands-on Python Engineer who can work independently with remote teams (SW, HW, logic,) and create products that will shape the future of Quantum Computers.
The Quantum Computing SDK is the interface through which our customers run our control system. Customers use it to configure their cutting-edge system and run their ground-breaking experiments. Various institutions from world-class universities to hyper-scalers use the SDK to calibrate their delicate QBits, perform Write and Read Quantum Computing Operations and run programs in higher level Quantum Computing languages like OpenQASM3.
Responsibilities:
Develop the software for the company's Quantum Computing SDK.
Take part in all the technical aspects of the SW development from design to delivery.
Work with high standards of SW methodology, clean-code and CI.

We are seeking an experienced Software Engineer to join the NVLINK NOS group, developing the NVLINK switch Operation System (OS). In this role you will be playing a major role in developing our OS which is critical to NVIDIA's next generation networking technologies, and enable large-scale deployment in High-Performance Computing (HPC) data centers. Are you passionate about working on innovative technologies for next gen HPC? Then we want to hear from you!

What you'll be doing:
As a Software Engineer, you will use your expertise in Python and C++ to develop NVOS features in an Agile methodology.
Owning and leading the development of major features end-to-end, trough its entire life cycle.
Being actively hands-on in OS software coding and debugging.
Support customers integration with our NVLINK technology.
Collaborating with off-shore teams.

Required Micro-Architect
Description
A global leader in control systems for quantum computing, a field on the verge of exponential growth.
Our innovative hardware and software mark a groundbreaking approach in quantum computer control, scaling from individual qubits to expansive arrays of thousands.
At our core lies a passionate and ambitious team committed to reshaping the construction and operation of quantum computers.
Our work is fueled by a deep understanding of customer needs, driving us to deliver unparalleled solutions in this revolutionary field.
Join our cutting-edge hardware development team as Micro-Architect and play a key role in defining and implementing the micro-architecture of advanced digital logic components.
What You'll Do:
Define and develop micro-architecture for complex logic blocks - from concept through high-quality RTL implementation
Collaborate closely with architecture, verification, design and software design teams
Write clear and detailed design specifications and drive architectural trade-off analysis
Optimize for performance and area
Contribute to innovation, methodology improvements, and technical leadership within the team.

We are looking for an excellent design engineer to join our team and build our state-of-the-art control and orchestration platform. We are looking for a highly talented and motivated person, who is a real team player and which can collaborate closely with engineers from other disciplines and quantum physicists
Responsibilities:
Learning system and SW requirements for proper implementation of HW-SW interface
Designing a configurable and very low-latency challenging RTL
Bringing the state-of-the-art FPGA to its limits with regards to logic & timing optimization
End2end ownership of the entire coding process (Arch->uArch->Design->Implementation).

We are looking for a highly experienced Backend Developer - Design and develop the core backend software layer over the company's specialized flagship product. It is a unique opportunity to join a team of top-notch engineers and work on cutting-edge technologies in a fast-paced environment of quantum computation.
What Makes This Role Different:
Our backend team sits in the middle of everything - we're the orchestration layer between:
Hardware control systems (C++)
Client exposed SDK (Python)
Reporting and managing system (Go)
Our business logic (Java/Kotlin + Spring)
What this means for you:
You'll own features end-to-end - from design conversations to production, across multiple systems and teams
You'll collaborate constantly - with engineers working in different languages, explaining APIs, debugging integration issues together
You need to think in systems - your code is one piece; you need to understand (and care about) how it all fits together
When something breaks, you dig in - even if the bug is in Python code you didn't write, or a timing issue between services
You make decisions - sometimes with incomplete information, and you take responsibility for the outcomes
You'll Thrive Here If You:
Ask questions when requirements are unclear rather than guessing
Help teammates when they're stuck, and ask for help when you are
Balance "perfect" with "good enough to ship"
Communicate clearly in English (written and verbal)
Think beyond your code and take ownership without being asked.

Our Professional Services is seeking a data Analyst!?Key Responsibilities:
* Analyze large datasets and generate actionable insights to improve business processes, with a particular focus on marketing activities and performance.
* Develop and execute advanced SQL queries for data extraction, analysis, and reporting from multiple data sources.
* Define, design, and build panels and data structures to be integrated into campaign management systems and dashboards.
* Measure and analyze campaign effectiveness, including producing performance reports and recommendations.
* Lead end-to-end data deliverables - from business and technical requirements gathering through implementation.
* Work cross-functionally with business stakeholders, data teams, and development teams to support ongoing initiatives.

We are looking for an experienced Front-End Team Leader to lead the design and development of the companys user-facing software systems. This is a unique opportunity to combine hands-on technical leadership with people leadership, working closely with product, UX, and backend teams to build sophisticated, high-impact user interfaces for cutting-edge quantum computing platforms.
Join us in this exciting journey to redefine the future of quantum computing.
Responsibilities
Lead and mentor a global team of front-end engineers, fostering technical excellence and growth.
Own the front-end architecture and technical vision of complex web applications.
Design and implement scalable, high-performance, and maintainable UI solutions.
Collaborate closely with backend, product, UX, and system engineers to deliver end-to-end features which are perfectly adapted to the needs of the Quantum Computing audience.
Drive best practices in code quality, testing, performance, and accessibility.
Take part in hands-on development alongside the team.
Lead design reviews, code reviews, and technical decision-making.
Execute in a fast-paced, evolving environment with high technical complexity.

We are looking for a hands-on Embedded Tech Lead to manage a team of 2-3 engineers specializing in low-level embedded development, as part of the embedded team. This role involves low-level SW design on complex HW & Logic, board- and platform-level prototyping, and tight integration with FPGA/RTL logic.
You will collaborate closely with hardware, FPGA/RTL, software, and system teams across multiple sites to deliver cutting-edge embedded solutions that power quantum control systems.
Responsibilities
Lead and mentor a team of 2-3 low-level embedded engineers within the broader embedded development team.
Drive board-level and platform-level prototyping, bring-up, and validation for new embedded platforms.
Develop, integrate, and maintain low-level drivers and system-level embedded software.
Collaborate with FPGA/RTL team to integrate logic components into the embedded platform.
Own and execute system bring-up activities, including debugging HW/Logic/SW interfaces.
Take part in system-level architecture and cross-team design definitions.
Conduct technical reviews, establish best practices, and help shape the direction of the low-level embedded domain.

Software team leader - Smart Energy Solutions A global technology company in the smart energy sector is looking for an experienced Software team leader to drive the development of advanced energy management solutions. The company operates internationally and develops innovative systems that combine software, hardware, and AI technologies to support clean and efficient energy usage worldwide.

Key Responsibilities:
Lead a team of software engineers in the design and development of smart energy management solutions connecting devices through advanced communication protocols.
Collaborate closely with system engineers and software architects to ensure scalable, secure, and high performance architecture aligned with the product roadmap.
Take an active hands on role in development, conduct code reviews, and enforce best practices for quality and maintainability.
Leverage AI based tools and methodologies to accelerate development and enhance code quality.
Oversee development across multiple Embedded Linux platforms and mentor team members toward technical excellence.

We are looking for a highly experienced a hands-on Compiler Engineer who embodies ambition and positivity.
Someone who can passionately take ownership of their responsibilities, collaborating effectively with remote teams to not only meet but exceed our objectives and fulfill the evolving needs of our expanding customer base.
Responsibilities:
Develop our compiler from a proprietary quantum language to a proprietary processor tailored to realize and accelerate quantum computing.
Take on complex optimization challenges at the core of our unique compiler, focusing on real-time applications, hybrid quantum/classical algorithms, and parallel processing.
Conduct rigorous testing, debugging, and profiling to ensure the performance and correctness of compiler outputs.
Hands-on development and debugging of software to optimize the utilization of limited hardware resources, enabling the scaling of quantum computing systems and improving quantum algorithm performance on our cutting-edge quantum orchestration platform.
Collaborate closely with hardware, software and architecture teams to ensure seamless software-hardware integration, directly enhancing system capabilities and performance.

Required Research Scientist - LTX Model Quality
The role
Following the success of LTX-2, our widely adopted open-source text-to-audio+video model, we are expanding our efforts to develop cutting-edge audio+video generation models and are hiring Research Scientists to join our LTX-Applications team.
As a Research Scientist in the LTX Model Quality team, you will play a key role in elevating the quality, controllability, and alignment of our video generation model. This role focuses on the critical post-training phase-developing and implementing techniques such as preference optimization, reward modeling, and human feedback integration to refine model outputs. You will design robust evaluation frameworks, define quality metrics, and build systematic approaches to identify and address model failure modes. Your work will directly impact the quality of the videos we generate.
What you will be doing
Develop and implement post-training pipelines, including RLHF, DPO, and other preference-based optimization techniques for video generation models.
Fine-tune and control VLLMs for video and audio understanding.
Design and iterate on quality evaluation metrics and frameworks.
Conduct systematic failure mode analysis and develop targeted interventions to address quality gaps.
Build and curate high-quality preference datasets and evaluation benchmarks that capture nuanced aspects of video generation quality.
Collaborate closely with fellow researchers to establish tight feedback loops between human judgment and model improvement.

Required Senior Software Engineer - Research
What you will be doing
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 our 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 our 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

Required Research Scientist - Audiovisual Understanding, Model Foundations
Team & role
The Core Generative AI team is a unified group of researchers and engineers dedicated to developing our generative foundational models that serve LTX Studio, our AI-based video creation platform. Our focus is on creating a controllable, cutting-edge video generative model by merging cutting-edge algorithms with exceptional engineering. This involves enhancing machine learning components within our sophisticated internal training framework, crucial for developing advanced models. We specialize in both research and engineering that enable efficient and scalable training and inference, allowing us to deliver state-of-the-art AI-generated video models.
As a Large Scale Video Understanding Research Scientist, you will play a key role in improving video generation quality and efficiency by improving video and audio understanding pipelines used for both training data construction and model evaluation.. This role demands hands-on work with large-scale Video Language Models (VLLMs), including fine-tuning, post-training, and control, alongside implementing classic computer vision and signal processing algorithms and applying strong research skills. Your expertise in post-training and controlling large scale foundational models, understanding statistics, implementing complex systems and eliminating bugs will be crucial, as our video training sets consist of petabytes of data processed across hundreds to thousands of virtual machines.
What you will be doing
Fine-tune and control VLLMs for video and audio understanding.
Design algorithms for balancing, filtering, and curating training and evaluation datasets, informed by model behavior and failure modes.
Implement classic and modern algorithms for processing, clustering, evaluation and filtering of large scale datasets.
Work within high-performance, scalable distributed systems capable of handling petabytes of data, with attention to throughput, correctness, and reproducibility..
Collaborate with other researchers and product stakeholders to iteratively improve training sets and evaluation protocols through tight feedback loops driven by model performance.

Required Research Scientist - Audiovisual Generation, Model Foundations
The role
Following the success of LTX-2, our widely adopted open-source text-to-audio+video model, we are expanding our efforts to develop cutting-edge audio+video generation models and are hiring Research Scientists to join our LTX-2 Core team.
Weve been at the forefront of innovation in text-to-image and text-to-audio+video generation, with LTX-2 driving our flagship product, LTX Studio, and gaining significant traction in the research and open-source communities, including integrations with platforms like ComfyUI and Diffusers.
This role focuses on pioneering model architecture and pre-training algorithms, shaping the next generation of our foundational generative AI models.
What you will be doing
Pre-train and fine-tune video, audio, and image generative models to pursue state-of-the-art results.
Publish papers and open source models to benefit the research community and advance the field.
Design and implement machine learning models for text-to-audio and text-to-video generation.
Collaborate with data engineers to curate and preprocess text and video data.
Optimize models for high performance, ensuring efficient training and inference.
Build new controls and capabilities into generative text-to-audio and text-to-video models.
Stay updated with the latest developments in Generative AI, particularly in the fields of image, video, and audio.
Work closely with product teams to integrate AI models into applications and services.
Conduct experiments and prototype new concepts to advance the capabilities of our AI tools.

Required Large Scale Training Engineer - LTX Model
About the Role
As a Large Scale Training Engineer, you will play a key role in enhancing the training throughput of our internal framework and enabling researchers to pioneer new model concepts. This role demands excellent engineering skills for designing, implementing, and optimizing cutting-edge AI models, alongside writing robust machine learning code and understanding supercomputer performance deeply. Your expertise in performance optimization, understanding distributed systems, and bug elimination will be crucial, as our framework supports extensive computations across numerous virtual machines.
This role is designed for individuals who are not only technically proficient but also deeply passionate about pushing the boundaries of AI and machine learning through innovative engineering and collaborative research.
Key Responsibilities
Profile and optimize the training process to ensure efficiency and effectiveness, including optimizing multimodal data pipelines and data storage methods.
Develop high-performance TPU/GPU/CPU kernels and integrate advanced techniques into our training framework to maximize hardware efficiency.
Utilize knowledge of hardware features to make aggressive optimizations and advise on hardware/software co-designs.
Collaboratively develop model architectures with researchers that facilitate efficient training and inference.
Design, maintain, and evolve a high-quality, shared codebase that emphasizes correctness, readability, extensibility, testing, and long-term maintainability, while balancing performance requirements.