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We are seeking a motivated MSc student to join our R&D team as a Machine Learning Engineer focusing on medical image processing (CT, MRI). In this role, you will support the development and optimization of deep learning models for image segmentation and analysis, leveraging U-Net and 3D U-Net architectures.
This is a hands-on opportunity to work on real-world clinical data and contribute to next-generation solutions for diagnostic and procedural planning workflows.
How you will make an impact:
Model Development:
Assist in designing and implementing deep learning models for medical image segmentation using U-Net, 3D U-Net, and nnU-Net frameworks.
Support optimization of models for volumetric CT/MRI datasets.
Data Handling & Processing:
Develop preprocessing pipelines (normalization, augmentation, resampling).
Integration & Experimentation:
Support integration of models into research pipelines using tools like MONAI and 3D Slicer.
Run experiments, evaluate model performance, and document results.
Collaboration:
Work closely with engineers, data scientists, and clinical teams.
Participate in technical discussions and contribute ideas for improving model performance.
Research & Innovation:
Stay updated on state-of-the-art methods in medical imaging AI and segmentation.
Explore improvements in model architecture and training strategies.

We are seeking an experienced RF Systems Engineer to lead the RF domain within the hardware team, for the development of advanced communication systems.
This role includes full professional ownership of RF and antenna domains across the company- from architecture definition, through hands-on development and testing, to integration and technological leadership.
This is a key position with deep involvement in hands-on development, intended for an engineer with extensive practical experience, strong technical leadership skills, and attention to detail.
Job Description:
Professional leadership of the RF domain within the hardware team
Hands-on design and development of RF systems for advanced communication systems
Design, simulation, and optimization of antennas and antenna arrays
Definition of RF architecture and communication chains
Integration, calibration, RF testing, and hands-on troubleshooting in the lab
Daily work with advanced RF equipment, including measurements and performance analysis
End-to-end responsibility for RF system performance
Cross-functional work with hardware, software, mechanical, and algorithm teams
Technological leadership and professional support for development teams
Work with vendors and subcontractors in RF and antenna domains.

A defense high-tech company, is looking for a Final Test Technician to join the operations final testing team.
Job Description:
Perform electrical testing on subsystems and systems during the production process
Test electronic boards, subsystems, cameras, sensors, and other components
Perform system-level testing down to the component level
Troubleshoot and investigate faults in electronic systems.

We are seeking a Platform Engineering Group Lead to strengthen our platform and operational engineering capabilities and ensure the company has a secure, reliable, and scalable foundation for product delivery and operations. This role drives execution, raises engineering standards, and improves consistency across deployment, infrastructure, and operational practices in support of product delivery, customer environments, and internal platforms. The role partners closely with R&D, QA, IT stakeholders, and PS/CS to enable consistent deployments through standards, reference architectures, and high-quality installation documentation.
Your key responsibilities will be:
Lead the Platform Engineering group, including people leadership, prioritization, execution management, and cross-functional coordination, and establish an effective operating cadence for a small, high-impact organization.
Build scalable operating models, ownership boundaries, and execution discipline across platform, deployment, and operational engineering activities.
Drive automation and deployment engineering outcomes across CI/CD, release readiness, environment provisioning, and delivery tooling, with a strong focus on reducing manual steps and operational risk.
Own deployment readiness across internal and customer-facing environments, including staging deployments, validation steps, installation packages, and deployment runbooks, to support consistent and repeatable implementations.
Ensure effective internal infrastructure and workplace technology operations, including service levels, escalation paths, operational hygiene, endpoint lifecycle, backups, and core office/server-room infrastructure.
Drive security and compliance readiness within the groups scope, including operational controls implementation, remediation tracking, evidence discipline, and coordination with external cybersecurity partners and internal security stakeholders.
Establish engineering standards and technical guardrails across infrastructure-as-code, change management, observability, access controls, and backup/restore verification.
Lead incident management across platform, infrastructure, and internal technology services, including issue assessment, prioritization, escalation, incident reviews, and corrective actions to improve reliability over time.
Define and improve deployment patterns, reference architectures, and environment recommendations based on customer constraints and operational requirements to support successful PS/CS engagements.

We are looking for a talented and passionate Full Stack Software Engineer to join our growing R&D team and help build next-generation data and AI-driven products.
In this role, you will take part in designing and developing scalable, high-performance web applications while working with modern technologies, advanced development methodologies, and cloud-native architectures. You will collaborate closely with Product, UX, QA, and fellow engineers to deliver exceptional user experiences and innovative solutions.
If you enjoy solving complex technical challenges, exploring new technologies, and working in a fast-paced environment where your impact is significant, wed love to meet you.
What Youll Do
Design and develop modern, scalable web applications from end to end.
Build robust backend services and APIs using modern server-side technologies.
Develop rich, responsive, and high-performance frontend applications.
Translate product and UX requirements into clean, maintainable, production-grade code.
Participate in architecture and technical design discussions.
Work with AI-powered technologies and modern data platforms.
Collaborate closely with Product Managers, UX Designers, QA Engineers, and other developers in an agile environment.
Continuously improve code quality, development processes, and engineering standards.
Explore and adopt new technologies, tools, and development approaches.
Who You Are
A fast learner who quickly adapts to new technologies and challenges.
Curious, innovative, and passionate about technology.
A team player who enjoys brainstorming and collaborative problem-solving.
Comfortable working with both modern and legacy systems.
Motivated to create impactful products with a great user experience.
Someone who thinks outside the box and brings creative solutions to complex challenges.

Required Product Manager - Storage Networking Platform
The Role
This is a rare opportunity to:
Have a direct impact on AI performance and GPU efficiency at scale
Combine deep technical thinking with product ownership
Own product decisions that influence real-world system behavior
As a Product Manager, you will define how next-generation AI workloads interact with high-performance storage and networking systems.
This is a deep-tech product role at the core of our platform, where your decisions directly impact performance, scalability, and efficiency across large-scale AI environments.
Youll operate at the intersection of product, distributed systems, and hardware-aware infrastructure - shaping how modern data platforms are built and optimized.
What You'll Do:
Define and execute product strategy for our platform and infrastructure layer
Own the product roadmap - balancing innovation, performance, and customer needs
Work closely with engineering to design and deliver high-performance capabilities
Translate complex technical challenges into clear product decisions and priorities
Partner with customers and internal teams to understand real-world use cases and constraints
Stay ahead of trends in storage, networking, and distributed systems
Collaborate with top engineers, architects, and customers solving cutting-edge challenges.

Required Software Engineer - Verification and Reliability
The Mission
We are building NeuralMesh- the worlds first intelligent, adaptive mesh storage system. To ensure our platform is unbreakable for the worlds largest AI and GPU clusters, we don't just "test" our code. We build an adversarial distributed system as complex and sophisticated as the product itself.
We are moving away from traditional QA automation. We are building a high-octane engineering force that treats reliability as a high-end software problem. We need "Quality Hackers" who want to build the technology that proves bugs don't exist.
In this role as a Software Engineer in Test (SET), you are a developer first. You will join a high-impact team of engineers who write production-grade code to build a massive-scale validation ecosystem. Your job is to act as "The Breaker"-designing the infrastructure, chaos experiments, and AI-driven tools that push our platform to its theoretical limits.
What Youll Build:
Adversarial Engineering: Design and implement Python-based distributed frameworks capable of orchestrating millions of concurrent IO operations to hunt down race conditions and memory leaks.
AI-Augmented Validation: Be at the forefront of the AI-Native transformation. You will leverage LLMs and Generative AI to automate complex scenario generation, build intelligent agents for root-cause analysis, and multiply your engineering velocity.
Simulation & Chaos: Build the "Entropy Engine." You will develop tools that inject real-world failures - latency, packet loss, and hardware crashes - to prove the resilience of our Raft and RDMA implementations.
Deep-System Observability: Move beyond "Pass/Fail." You will build telemetry pipelines to track P99 latency and jitter, providing critical architectural feedback to the Core Kernel teams.
Collaborative Architecture: You will operate with the same rigorous standards as the Core R&D team: design docs, production-grade code reviews, and high-level architectural planning.

Required Senior Software Engineer, Filesystem
What you'll be doing:
The filesystem group is a high-powered team responsible for implementing algorithms at scales of 100s of PBs. The team also manages the core filesystem components, including blocks and metadata management, snapshots, RAID logic, object-store tiering, unique cloud disaster recovery features, and more. And most importantly, they skillfully handle the most delicate part of the solution - our customers data.
As a Senior Software Engineer, youll:
Design and develop distributed file system components to support data management features such as snapshots, replication, tiering, and advanced data reduction algorithms;
Participate in the design, architecture, and implementation of next-generation storage architecture;
Assist in technically managing initial storage implementations including proofs-of-concept;
Diagnose bottlenecks and implement clean and performant solutions to achieve unbeatable performance;
Design algorithms and data structures to make sure customer data is safe and coherent across our solution in a wide variety of failure modes; and
Constantly revisit the architecture, algorithms, and methodologies to improve productivity, reliability, and maintainability.

Required Senior Software Engineer, Control
As a Senior Software Engineer, youll:
You will be responsible for building the "brain" of our main product, which is a distributed file system -the layer that manages orchestration, metadata, cluster membership, and implements complex logic required to manage hundreds of thousands of nodes, for cluster scaling, automated failover, zero-downtime rolling upgrades and "self-healing" to detect and remediate hardware failures or network partitions.
Design, implement, unit test, and maintain services that coordinate and the cluster
Optimize Performance: Work with complex data structures like spanning trees or LSM-Trees, concurrency control mechanisms (MVCC) to improve speed and efficiency.
Collaborate closely with cross-functional teams to translate backend capabilities into real-world impact.

We are seeking a Senior Engineer for our Labs (on premise) Team member, working with a team of engineers, who manage our physical labs. You'll support the infrastructure for our servers, both HW and SW wise. This role offers an exciting opportunity to take a significant part of ensuring optimal testing environments for our enterprise-grade storage solutions.
Requirements:
- Hands-on work in a data center environment: racking, cabling, replacing hardware components, and troubleshooting server failures
- Design and implement infrastructure to allocate, configure and troubleshoot servers
- Daily operational support for servers, switches, and lab infrastructure
- Building and maintaining Linux images for servers and lab environments
- Working with a mix of modern and legacy systems in a lab environment
- Supporting VMware-based infrastructure and virtualization environments
- Work with multiple teams on gathering requirements and coordinating changes
- Define and implement infrastructure monitoring strategies using modern observability tools
- Drive infrastructure modernization initiatives and best practices adoption
- Establish and maintain documentation for lab processes, infrastructure, and operational procedures
- Perform capacity planning and resource allocation for lab environments
- Working closely with procurement, vendors, and external technicians
- Participating in on-call rotation (small team, occasional incidents)
Occasional travel to the US (1-2 times a year).

Required Performance Engineer
About the role;
Were building a next-generation platform for validating large-scale distributed systems. Our goal is to continuously ensure the correctness, performance, and resilience of the Data Platform across every layer of the stack.
As a Senior Software Engineer, youll work hands-on on the systems and frameworks that test, stress, and validate complex distributed infrastructure under real-world conditions. Youll help design and build automated environments that simulate scale, concurrency, and failure scenarios, and youll contribute to evolving how we ensure reliability and correctness in modern infrastructure systems.
This role is ideal for engineers with a strong distributed systems background who enjoy deep technical problem-solving, working close to the system, and building tools that improve quality, stability, and confidence at scale.
What Youll Do:
Design and implement core components of a distributed testing infrastructure and quality platform.
Build automated frameworks to validate functionality, performance, and resilience at scale.
Collaborate closely with infrastructure, storage, and platform teams to ensure quality is built into the development lifecycle.
Contribute to improving tooling, test coverage, and engineering best practices across the organization.

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.