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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.

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.

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 a passionate and experienced Software Engineer (C/C++) to join our vibrant Networking Group.
In this role, you will play a key part in designing and developing our high-performance and highly-scalable backbone platform.
Responsibilities:
End-to-end ownership of solution delivery: from design, implementation to testing, rollout and monitoring
Drive highly performant and highly efficient designs
Leading collaborative efforts with cross-functional teams.

We are looking for an AI Builder to design, build, and maintain agentic AI-driven workflows that streamline and automate internal business processes across the company.
This role focuses on initiating and orchestrating AI agents, integrating them with existing systems, and reducing manual effort across Sales, Marketing, Order Management, Finance, HR, and more.
You will work closely with the Information Systems team and business stakeholders to turn repetitive, human-dependent processes into reliable, AI-powered flows.
This is a hands-on builder role, not a research or pure data science position.
Key Responsibilities:
Agentic AI & Automation:
Design and implement agent-based AI workflows to automate internal processes end-to-end
Build multi-step AI agents capable of:
Decision-making
Tool usage (APIs, SaaS tools, internal systems)
Escalation and exception handling
Continuously optimize AI flows to reduce human involvement while maintaining control and auditability
AI Tooling & Platforms:
Implement solutions using Agentic AI platforms, tools and frameworks, such as: OpenAI / Azure OpenAI / Copilot Studio / Gemini Enterprise, AWS bedrock (AgentCore), SFDC Agentforce
Low-code / no-code automation tools with AI capabilities (e.g., Make, Workato, UiPath, n8n)
Select and evaluate new AI tools to support internal automation initiatives
Systems Integration:
Integrate AI agents with internal systems such as: CRM (SFDC), ERP (NetSuite), ticketing systems (Jira)
Identity and access management
Monitoring, logging, and knowledge bases
Build and consume APIs to enable agent actions and data retrieval
Governance, Reliability & Security:
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.

Were looking for a Senior Software Developer who combines strong technical skills with product intuition and a sense of ownership. Youll work across the stack - from infrastructure to backend services and intuitive UI/UX - building scalable, high-impact systems that shape how organizations secure their AI.
What youll do
Own and run major features and subsystems end-to-end - youll take ideas from concept to production and beyond (monitoring, iteration, refinement).
Work across the full stack: infrastructure, platform, backend services, APIs, and UI/UX. Youll be comfortable shifting between how do we deploy this reliably to how does the user experience this.
Drive team culture of ownership, craftsmanship, iteration and delivery: were not just about shipping features but owning the outcome, learning fast, and improving continuously.
Mentor and support other engineers: bring in the best practices of maintainability, scalability, reliability, and product thinking.

The Role Were looking for a Mid-Level DevOps Engineer to join our growing team and take part in designing, building, and operating scalable, secure, and automated AWS-based infrastructures. Youll work in a fast-paced environment, using advanced, cloud-native technologies, and have direct interaction with customers - understanding their challenges, designing solutions, and guiding them from architecture to production. Responsibilities Build and manage Infrastructure as Code (IaC) using Terraform Develop and optimize CI/CD pipelines (GitLab CI, GitHub Actions, Jenkins, etc.) Design, deploy, and maintain containerized environments using Docker & Kubernetes (EKS) Design and implement scalable, secure, and cost-efficient AWS architectures Work directly with customers to gather requirements, design solutions, and provide hands-on technical guidance Lead and support cloud modernization projects, including migrations and replatforming Monitor and improve system reliability using observability tools Troubleshoot complex production issues in dynamic, high-velocity environments Apply cloud security best practices (IAM, encryption, networking, compliance)

We are a fast-growing deep-tech startup, currently expanding following a new funding round, developing cutting-edge sensing and signal intelligence technologies.

Develop and maintain a B2C Flutter mobile app with strong focus on performance, scalability, and UX Build new apps based on existing architecture and codebase Ensure cross-device compatibility, accessibility, and responsiveness Translate product vision and Figma designs into clean, scalable, maintainable code Support and improve CI/CD pipelines (Azure)

company description
we are the global leader in identity security. centered on privileged access management, we provide the most comprehensive security offering for any identity - human or machine - across business applications, distributed workforces, hybrid cloud workloads and throughout the DevOps lifecycle. the worlds leading organizations trust us to help secure their most critical assets. to learn more about us , visit our blogs or follow us on x, linkedin or facebook. job description
we are looking for a bright, talented senior devex platform Developer to join a team of highly energized and professional engineers working on mission-critical systems in the red-hot cybersecurity industry. this role is focused on development flow productivity and building application infrastructures and tools to handle the challenges of hyper-growth and application scale.
you will design, implement, and deploy products and infrastructures that directly increase our stability and quality while reducing our time to market.
what you will do:
Developer platforms: design and develop solution-oriented enterprise DevOps platforms and tools to improve the Developer experience.
velocity & quality: create solutions to increase r&d velocity, reduce lead time, and improve overall product quality.
saas infrastructure: plan, design, and develop company's saas infrastructure, operation engine, and deployment strategy.
ci/cd & security: develop and adopt new technologies to improve ci/cd pipelines, utilizing a devsecops "shift left" approach to introduce security early in the cycle.
troubleshooting: perform platform and service troubleshooting across various applications, domains, and platforms.

we are the global leader in identity security. centered on privileged access management, we provide the most comprehensive security offering for any identity - human or machine - across business applications, distributed workforces, hybrid cloud workloads and throughout the DevOps lifecycle. the worlds leading organizations trust our company to help secure their most critical assets.
job description
as a staff engineer in the data & ai platform group, you will be a senior technical leader responsible for driving the design, implementation, and delivery of complex, high-impact features across our data and ai ecosystem. you will set engineering standards, lead cross-team initiatives, and provide hands-on technical guidance to developers working on large-scale, cloud-native distributed systems.
this role combines deep technical expertise with leadership: shaping the platforms architecture, mentoring senior engineers, and ensuring technical excellence and execution. in this role you will
lead end-to-end development of high-priority, cross-team features and initiatives in the data & ai platform. design and implement scalable, resilient, and secure distributed systems in a modern cloud environment. drive technical decision-making, influence architecture directions, and collaborate closely with product, data engineering, and ai teams. mentor developers, support their growth, and elevate engineering practices across the group. promote engineering excellence through code reviews, design reviews, and continuous improvement initiatives. evaluate new technologies and guide their adoption where appropriate. collaborate with engineers and managers across our company to align standards, share knowledge, and lead technical deep dives

we are seeking for a highly motivated and experienced senior backend Developer to join our group.
as a senior Developer in our group, you will design and build our new high scale, complex, cutting-edge systems built in React & Python running over aws, full ci/cd using cdk. you will enjoy both infrastructure and applicative challenges.
practice all software development life cycle in agile oriented environment
design and implement the infrastructure of the system
research and implement sophisticated Cyber security mechanisms
explore new technologies and tools to keep us using cutting edge solutions
help guide and contribute to feature design and implementation to bring the product to the next level.
participate in continuous and iterative engineering cycles with emphasis on code quality, supportability, scalability and performance qualifications
loves technology and excited about learning new stuff
3+ years of experience in Python /go/node/ruby/ JAVA ( Python is a definite advantage)
desire to use new technologies and understand them in depth
passionate about code design, high-quality code, and code reviews, optimizing and challenging the status quo
proactive by nature, internal drive for excellence and improvement
good communication skills, fluent in english, good writing skills
at least 4 years of sw development experience
bachelors degree in Computer Science or engineering related field / technology elite unit alumni with relevant experience

company description
we are the global leader in identity security. centered on privileged access management, we provide the most comprehensive security offering for any identity - human or machine - across business applications, distributed workforces, hybrid cloud workloads and throughout the DevOps lifecycle. the worlds leading organizations trust us to help secure their most critical assets. to learn more about us, visit our blogs or follow us on x, linkedin or facebook. job description
the role
we are seeking a senior platform engineer to join our platform team. you will be responsible for building the technical foundation that hundreds of developers will use daily.
your goal is to make kubernetes "invisible" for our developers. you will design and implement the automated machinery-the "paved road"-that enables application teams to move from code to production securely and reliably, without managing the underlying infrastructure themselves.
responsibilities
platform engineering & automation
internal Developer platform (idp): build and maintain our Developer portal, creating a unified "single pane of glass" for service catalogs, self-service actions, and scorecards. k8s core: design, implement, and maintain production-grade kubernetes clusters with a focus on multi-tenancy, security, and high availability. gitops mastery: implement and manage automated deployment workflows using gitops principles (argocd or flux). self-service apis: create abstractions (using tools like crossplane or custom cli tools) to simplify cloud resource provisioning and integrate them directly into idp. Developer experience (devex)
workflow optimization: analyze the Developer 's "inner and outer loops" to identify friction points and automate them away via the idp. standardization: create helm charts, ci/cd templates, and "gold path" configurations that embody best practices for security and observability. technical mentorship: act as a subject matter expert for r&d teams, providing guidance on containerization, microservices architecture, and cloud-native patterns. operational excellence
observability: build comprehensive monitoring and logging stacks (prometheus, grafana, opentelemetry) and surface these metrics within idp to give developers deep insights. security & compliance: implement automated policy enforcement (opa/kyverno) and ensure all platform components adhere to identity security standards. infrastructure as code: maintain 100% of the platform via iac tools like terraform/pulumi/opentofu etc. qualifications
technical