Location: San Francisco; Palo Alto; New York City
We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL - and we need another engineer to join us.
WHAT YOU WILL WORK ON
Examples of real work the team does:
- New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway.
- GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow.
- Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic.
- Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernel interleaving.
- Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents.
WHO WE'RE LOOKING FOR
- Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus.
- You understand modern LLM architectures and are able to bring them up reliably in a production environment.
- You've built and operated production distributed systems under real load - ideally performance-critical ones.
- Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels.
- You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday.
- Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you.
GOOD IF YOU TOUCHED ANY OF
- ML compilers and framework internals: PyTorch internals, torch.compile, custom operators.
- Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism.
- Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving.
- Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis.
- Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads.
QUALIFICATIONS
- 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.
- Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow).
- Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores).
- Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).
Location: London
We are looking for an AI Inference Engineer to join our growing team. We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL.
RESPONSIBILITIES:
- New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway.
- GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow.
- Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic.
- Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernels interleaving.
- Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents.
WHO WE'RE LOOKING FOR:
- Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus.
- You understand modern LLM architectures and are able to bring them up reliably in a production environment.
- You've built and operated production distributed systems under real load - ideally performance-critical ones.
- Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels.
- You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday.
- Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you.
NICE-TO-HAVE:
- ML compilers and framework internals: PyTorch internals, torch.compile, custom operators.
- Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism.
- Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving.
- Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis.
- Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads.
QUALIFICATIONS:
- 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.
- Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow).
- Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores).
- Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).
Final offer amounts are determined by multiple factors including experience and expertise.
Equity: In addition to the base salary, equity may be part of the total compensation package.
Location: London
We are looking for an AI Inference Engineer to join our growing team. We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL.
RESPONSIBILITIES:
- New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway.
- GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow.
- Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic.
- Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernels interleaving.
- Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents.
WHO WE'RE LOOKING FOR:
- Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus.
- You understand modern LLM architectures and are able to bring them up reliably in a production environment.
- You've built and operated production distributed systems under real load - ideally performance-critical ones.
- Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels.
- You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday.
- Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you.
NICE-TO-HAVE:
- ML compilers and framework internals: PyTorch internals, torch.compile, custom operators.
- Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism.
- Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving.
- Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis.
- Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads.
QUALIFICATIONS:
- 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.
- Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow).
- Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores).
- Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).
Final offer amounts are determined by multiple factors including experience and expertise.
Equity: In addition to the base salary, equity may be part of the total compensation package.
Location: Tbilisi, Georgia; Limassol, Cyprus
Workplace: hybrid
TradingView is the world’s largest financial analysis platform with more than 100M users across 180+ countries.
We build tools that help traders and investors make informed decisions — from advanced charting and market data to collaboration and publishing features. Our products are used daily by millions of individuals and trusted by companies like Revolut, Binance, and CME Group.
We’re continuing to grow and scale our platform, and we’re looking for people who care about product quality, take ownership of their work, and want to build systems used by a global audience.
About the team
Hi there! As we are growing, we need an experienced backend developer with a strong knowledge of Python to join our team. We have high traffic, and we value performance. We love clean code that works correctly and efficiently.
Your task will be to work with Django, design, and implement mechanisms for client-backend interaction, as well as monitor the performance of your code. You will work within the product team but with support from the company's leading Python developers.
If you love learning new things and have a broad technical outlook, we’d love to meet you!
Responsibilities
Breaking up the monolith & designing scalable microservices:
You won’t just be cutting chunks out of our Django monolith—you’ll be creating independent services for a distributed architecture that runs across multiple data centers worldwide. It’s a great chance to get into refactoring complex systems and learning best practices for building resilient services.
Developing & integrating new features in a high-load environment:
We’re talking about handling millions of simultaneous users—which means you’ll need to dive deep into backend performance, load balancing, API gateways, and monitoring tools. You’ll learn how to make services interact efficiently and ensure top-notch performance under real-world loads.
Building services that scale & stay secure:
You’ll design service architectures from scratch, pick the right data processing, messaging, and streaming solutions, and implement them. Working in a distributed environment, you’ll gain hands-on experience with Docker, Kubernetes, and other cool tech while learning how to build fault-tolerant systems.
Exploring different tech areas:
You won’t just be coding—you’ll also collaborate with infrastructure experts and dive into network protocols, traffic routing, load balancing techniques, and more. This is a great way to expand your skillset and understand not just backend development, but the bigger picture.
What makes you the perfect fit
5+ years of software development experience
Strong Python skills (2+ years of hands-on work)
Experience building high-load, fault-tolerant services
Good grasp of algorithms & data structures
Experience with Django & DRF
Ability to design solutions & choose the right tools
Broad knowledge of modern backend web technologies
Basic understanding of databases, messaging systems & data streaming
Experience with containerized infrastructure (Docker, Kubernetes)
Will be a plus
Experience in monitoring high-load production systems using monitoring tools such as Zabbix, Grafana.
Some experience with Go
Knowledge of Unix systems, OS internals & networking
Familiarity with frontend tech (JS, TS, React)
Experience in finance or trading domain
Familiarity with TradingView as a product
What we offer you
Flexible working hours and a hybrid work format
Well-equipped offices for focused and collaborative work
A global, distributed team of 500+ professionals
Learning, mentorship, and long-term career growth
Relocation support and private health insurance
Performance-based bonuses
TradingView Premium access
Regular team events and company-wide meetups
Join the TradingView team and help us build a product used by millions of traders and investors worldwide. We look forward to hearing from you!
TradingView is an equal opportunity employer. We embrace diversity and are dedicated to fostering a diverse and inclusive workplace. Our success is driven by 600+ professionals from 40+ countries who speak nearly 20 languages.
Location: Amsterdam, Netherlands; Germany; London, United Kingdom; Poland
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
We’re looking for a Senior Software Systems Engineer to join our team and play a key role in the development of our cutting-edge hyperscaler platform. The GPU & InfiniBand team is responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus on GPU computing, InfiniBand networks, and the KVM/QEMU stack. You’ll work closely with hardware virtualization and device emulation technologies, ensuring high performance and security in multi-GPU, HPC environments. The role involves analyzing, troubleshooting, and improving infrastructure to support new hardware, fine-tuning system performance, and automating fault detection and resolution in a complex system.
In this position, you will be responsible for:
Tuning the performance
of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments.
Analyzing and troubleshooting
the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions.
Integrating new hardware
into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM.
Enhancing automation systems
for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments.
Configuring and managing GPU devices
and InfiniBand fabrics, ensuring efficient and reliable operation.
We expect you to have:
5+ years of professional experience in
system-level software development
(focused on performance optimization, low-level programming).
3+ years of hands-on experience with
Linux systems
(administration, troubleshooting, and performance tuning).
In-depth understanding
of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems.
Strong proficiency in one or more
performance-oriented programming languages
(C/C++, Go, Python).
It would be a plus if you have:
Experience with
GPU end-to-end testing
in a
cluster environment
using InfiniBand networking.
Proven track record of analyzing and optimizing the performance of
HPC workloads
(e.g., simulations, data analysis, AI/ML workloads).
Familiarity with
RDMA, RoCE, and InfiniBand
protocols for high-performance communication.
Background in
Software-Defined Networking
(SDN) and experience with
HPC cluster networking
.
Understanding of
QEMU/KVM virtualization
and managing virtualized environments.
Experience with
deep learning frameworks
such as
PyTorch
and
TensorFlow
, and their integration with HPC systems.
Familiarity with
collective communication libraries
like
MPI
and
NCCL
for distributed computing.
We offer competitive salaries ranging from $170k-$300k + equity based on your experience.
We conduct coding interviews as part of the process.
#LI-LH2
Benefits & Perks:
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Location: India
Workplace: Remote
ClickHouse is the open-source, real-time analytical database behind a lot of today's AI. More than 4,000 companies build on ClickHouse, including Anthropic, OpenAI, Tesla and Meta.
As a Consulting Engineer, you're the hands-on engineer on our customers' most important projects. When a customer needs to migrate, integrate, or prove ClickHouse on a real workload, you work in the build alongside their engineers: you design it, build it, test it and hand it over.
You'll work on a broad mix of projects for customers across India, from moving large workloads off other databases to building new real-time analytics on ClickHouse. Each one is scoped with clear goals from the start, so you know what success looks like and can get stuck in. It's a fast way to build deep experience across lots of different data problems.
The consulting function at ClickHouse is less than a year old, so you'll help shape how ClickHouse delivers this work as the team grows. Between projects you take cases alongside support engineers, which keeps you close to day-to-day support.
WHAT YOU'LL DO
- Turn customer goals into a scoped project with measurable success criteria, sizing and a timeline
- Design a target architecture and prove it against the customer's own data: schema and engine design, capacity and sizing, proofs of concept
- Do the build: implementation, pipelines and integrations, migration execution, tooling and automation
- Measure it before it matters, with benchmarking, load and functional testing, then support the cutover
- Tune what production reveals, then hand over with an engagement report and knowledge transfer, so the customer's team can run it without you
- Take L1 to L3 cases alongside support engineers when you're between projects
- Feed what you see in the field back to Product and Engineering, and turn your work into reference architectures, knowledge base articles and blog posts
- Work in a constant feedback loop with the Pre-sales team to ensure that the demos and POCs they present are credible when you put them into production
WHAT YOU'LL BRING
- 5+ years delivering hands-on technical work for customers, whether your title was consultant, professional services, solutions architect, senior support, SRE or something else
- Real depth in databases, whether analytical, transactional or relational
- Hands-on SQL. You regularly write complex queries from scratch, and tune and debug them yourself
- You've owned implementations, migrations or POCs for external customers from start to finish
- Hands-on cloud experience (AWS, GCP and/or Azure)
- You've deployed and run workloads on Kubernetes yourself
- You've run distributed systems, such as distributed databases, in production
- You give precise technical answers and explain them clearly
- Fluent English
NICE TO HAVE
- Experience with ClickHouse
- Migrating analytical workloads from systems such as PostgreSQL, Snowflake, BigQuery or Elastic
- Terraform
- Data pipelines and streaming, such as Kafka, Kinesis, Spark or Debezium
- Python, Bash or Go
- Involvement in open source, as a user, contributor or community member
GOOD TO KNOW
- This role is remote in India
- Travel to customer sites is part of the job, up to 35% of your time, depending on the project: some need none, others weekly visits
- You'll join our India Support Services team, alongside Support Engineers and TAM Architects
- You'll be part of the on-call rotation, about one week a quarter, with time off in lieu if you're paged at a weekend
HOW WE HIRE
- A 30-minute call with our recruiter
- A conversation with the hiring manager
- A take-home exercise, designed to take three to four hours, with three working days to complete it
- A 90-minute technical interview with the team: you'll walk us through your take-home, then join a working session where you write and tune SQL live
- A final conversation with our VP of Support Services
- References, then an offer
The working session is without AI tools, so make sure you're comfortable writing queries from scratch. Download open-source ClickHouse and practise: it's free, easy to install, and great preparation.
PERKS
- Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries.
- Healthcare - Employer contributions towards your healthcare.
- Equity in the company - Every new eligible team member who joins our company receives equity.
- Time off - Flexible time off in the US, generous entitlement in other countries.
- A USD$500 Home office setup if you’re a remote employee.
- Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.
CULTURE - WE ALL SHAPE IT
As part of a rapidly scaling start-up, you will be instrumental in shaping our culture.
Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse.
EQUAL OPPORTUNITY & PRIVACY
ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.
Location: Warsaw
Workplace: onsite
With multiple awards to our name, Larian Studios has proven that we’re dedicated to delivering high-quality role-playing games As we move on to new projects, the studio that brought you Baldur’s Gate 3 & Divinity: Original Sin 2 is looking for a Senior Devops Full Stack Developer to join the team and help us in crafting the high calibre games our fans have come to expect.
Responsibilities
Work closely with other teams to design tools and improve the development process
Maintain and improve our internal libraries used across all our web applications
Design and implement pipelines to automate development processes
Extend, maintain and improve our existing tools
Provide support for other team members during critical stages of development
Requirements
Minimum 4 years programming experience
Good knowledge of full stack web programming (TypeScript, React, Node.js, MySQL)
Good knowledge of relational databases (RDBMs)
Good knowledge of scripting in ruby or python
Readiness to experiment with new technologies and software to meet development requirements and limitations
Good communication skills in spoken and written English
You are a team player and willing to take responsibility
This is a full-time, on-site role, requiring your presence in the office to support collaboration and creativity
Nice to Haves
Knowledge of Perforce
Experience in Game or Application development in C++
Experience with developing and hosting APIs in the Cloud
Knowledge of Kubernetes and Docker
Experience in a similar position in another game company
What we Offer
An international team of over 600 employees spread across 7 studios around the world, each of which have their own unique qualities, and maintain a small-studio feel
An open, collaborative environment where ideas are welcome and encouraged
A managerial team consisting of highly experienced game developers at the top of their fields
Sharing hobbies and passions with like-minded colleagues
Inclusive environment with many activities organized by the studios or the employees
Commitment to making the best game possible for the fans, including listening to community feedback
О ПРОЕКТЕ
Chrona agency ищет эксперта в инфраструктурную Web3-платформу, обслуживающую десятки тысяч блокчейн-нод в 120+ сетях (Ethereum, Solana, Cosmos и др.). Мы обеспечиваем 99.99% uptime для валидаторов и RPC-узлов, используя non-custodial модель.
ОСНОВНЫЕ ЗАДАЧИ
— Развертывание и эксплуатация блокчейн-нод различных типов (Validator, Archive, RPC).
— Обеспечение отказоустойчивости и минимального latency в геораспределенной инфраструктуре.
— Настройка мониторинга, алертинга и систем глубокой аналитики производительности.
— Автоматизация процессов обновления сетей и деплоя инфраструктурных компонентов.
— Работа с сетевой архитектурой (L2/L3) и оптимизация ресурсов кластеров.
— Применение SRE-практик для контроля SLA/SLO и планирования мощностей.
ТРЕБОВАНИЯ К КАНДИДАТУ
— Глубокий коммерческий опыт эксплуатации блокчейн-инфраструктуры.
— Экспертные знания Kubernetes в production-средах.
— Опыт работы с Terraform, Ansible и инструментами CI/CD (GitLab / GitHub).
— Уверенное владение стеком мониторинга: Prometheus, Grafana, Alertmanager.
— Глубокое знание Linux (Debian / Ubuntu) на системном уровне.
БУДЕТ ПРЕИМУЩЕСТВОМ
— Опыт работы с высоконагруженными RPC-сервисами.
— Понимание архитектур Proof-of-Stake (PoS) и механизмов консенсуса.
— Навыки построения отказоустойчивых кластеров в распределенной среде.
УСЛОВИЯ РАБОТЫ
— Полностью удаленный формат и отсутствие бюрократии.
— Выплаты в USDT согласно рыночной вилке.
— Возможность прямого влияния на архитектуру и масштабирование платформы.
— Работа в сильной инженерной команде с фокусом на результат.
Location: Amsterdam, Netherlands; Tel Aviv, Israel
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
Nebius is looking for
an experienced Security Architect Manager to lead our cybersecurity architecture function, with a strong focus on Kubernetes security, cloud infrastructure, cloud-native architectures, and secure software development.
The role is responsible for defining and implementing security architecture principles, designing secure cloud-native environments, and embedding security throughout infrastructure provisioning and software development lifecycles.
The successful candidate will combine deep technical expertise in Kubernetes and cloud security with proven team leadership, architectural design, and cross-functional collaboration skills. They will work closely with Cloud Engineering, DevOps, R&D, Platform Engineering, IT, and Security teams to ensure that security is built into the organization’s technology foundations.
Your responsibilities will include:
Cybersecurity Architecture
Define and maintain the organization’s cybersecurity architecture, reference architectures, security standards, and design principles.
Lead security architecture reviews for new systems, applications, infrastructure, and technology initiatives.
Translate threat models, business requirements, and risk assessments into practical security controls.
Establish security-by-design principles across cloud, infrastructure, application, and platform architectures.
Identify architectural security gaps and drive remediation roadmaps.
Kubernetes and Cloud-Native Security
Design and implement security architectures for Kubernetes-based environments and cloud-native platforms.
Secure Kubernetes clusters, control planes, worker nodes, namespaces, workloads, and cluster-to-cluster communications.
Define and enforce Kubernetes security best practices, including RBAC, workload identity, network policies, admission controls, Pod Security Standards, and secrets management.
Secure container images and registries, including image scanning, provenance, signing, and supply chain integrity.
Implement runtime security, workload isolation, threat detection, and monitoring for containerized environments.
Secure Kubernetes ingress, service-to-service communications, APIs, and service mesh architectures where applicable.
Establish security controls for container orchestration platforms across development, testing, and production environments.
Evaluate and manage Kubernetes security risks, misconfigurations, excessive privileges, exposed services, and vulnerable workloads.
Cloud Infrastructure Security
Lead security architecture across AWS and/or Microsoft Azure, including cloud-native and hybrid environments.
Define secure cloud landing zones, identity and access management, network segmentation, encryption, logging, and key management.
Implement preventive and detective security controls using cloud-native security services and centralized policy enforcement.
Drive cloud security posture management and remediation using CSPM, CNAPP, and related technologies.
Ensure alignment with organizational security requirements and relevant industry standards.
Secure Development and DevSecOps
Integrate security throughout the Software Development Life Cycle (SDLC), from design and coding to deployment and production operations.
Partner with R&D, DevOps, and Platform Engineering teams to embed security into CI/CD pipelines.
Define and implement automated security controls, including SAST, DAST, Software Composition Analysis (SCA), secrets detection, and container image scanning.
Establish secure coding standards, threat modeling practices, API security requirements, and secure software supply chain controls.
Promote developer-friendly security tooling and reusable security patterns that minimize friction and accelerate delivery.
Drive remediation of vulnerabilities and architectural weaknesses in collaboration with engineering teams.
Security Engineering and Risk Management
Develop technical security standards, architecture patterns, and security control baselines.
Conduct threat modeling, attack-path analysis, architecture risk assessments, and security design reviews.
Define security requirements for identity, access, data protection, network security, workload isolation, and observability.
Collaborate with Security Operations to improve security telemetry, detection capabilities, and incident readiness.
Evaluate emerging security technologies and recommend solutions based on risk reduction, operational effectiveness, and architectural fit.
Track security findings and drive measurable improvements in the organization’s security posture.
Team Leadership and Collaboration
Lead, mentor, and develop a team of cybersecurity architects and security engineers.
Define team strategy, technical priorities, delivery plans, and measurable performance indicators.
Build effective partnerships with Cloud Engineering, DevOps, R&D, Platform Engineering, and other technology stakeholders.
Communicate complex architectural risks and technical trade-offs to senior management and engineering leadership.
Foster a culture of engineering excellence, automation, accountability, and continuous improvement.
We expect you to have:
7+ years of experience in cybersecurity, security engineering, cloud security, or security architecture.
3+ years of experience managing technical teams or leading senior technical professionals.
Strong practical knowledge of Kubernetes architecture and container security in production environments.
Demonstrated experience securing cloud-native workloads and distributed systems.
Strong expertise in AWS and/or Microsoft Azure security architecture.
Hands-on understanding of Kubernetes RBAC, network policies, admission controllers, workload security, secrets management, and container runtime security.
Experience with Docker or other container technologies, Kubernetes deployment workflows, and container registries.
Strong understanding of cloud networking, IAM, encryption, key management, logging, and workload protection.
Practical experience with Infrastructure as Code and automated security controls.
Experience securing CI/CD pipelines and integrating security into software development processes.
Knowledge of threat modeling, vulnerability management, security architecture reviews, and risk assessment methodologies.
Proven ability to influence engineering teams and translate security requirements into scalable technical solutions.
Excellent communication skills in English.
Key Success Metrics
Improved security posture and reduced attack surface across Kubernetes and cloud environments.
Reduction in critical misconfigurations, excessive privileges, and recurring architectural vulnerabilities.
Increased adoption of secure-by-design architecture patterns across engineering teams.
Improved security coverage and automation across CI/CD pipelines and infrastructure provisioning.
Reduced time to remediate critical security findings.
Consistent implementation of Kubernetes and cloud security baselines.
Improved collaboration between cybersecurity, cloud infrastructure, platform, and development teams.
Development of a high-performing cybersecurity architecture team.
Benefits & Perks:
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Location: Hybrid
About Us
At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.
At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in.
Available Locations
Austin, US
Lisbon, Portugal
London, UK
NYC, US
About the Role
The Egress team was formed to own a very important aspect of Cloudflare's network-as-a-service: Egress connectivity for our vast portfolio of products.
As a member of the Egress team, you will be a key technical contributor to a cutting edge network software infrastructure used by a growing number of Cloudflare products to connect to any destination from Cloudflare's network. Among the products powered by this technology is WARP, our Zero Trust platform, and Cloudflare's egress proxy for the
iCloud Private Relay
product.
You will work closely with various Engineering teams to translate their requirements into new capabilities on the platform. Likewise you will partner with Network Engineering and SRE to ensure that the technology makes the best use of Cloudflare's world-class edge network.
You will participate in all stages of the software development lifecycle, from designing and documenting systems, to writing code and automated tests, to planning, managing, and monitoring production software deployments. You will work with a wide range of technologies and programming languages, including Rust, Go, Linux networking, ClickHouse, PostgreSQL, Grafana, Kubernetes, and more.
Engineering teams at Cloudflare operate a Run What You Build model, including ours. We are responsible for the health of our system and participate in our team's on-call rotation as part of operational responsibilities.
Because you’ll be solving problems of massive scale and significance, you are a growth-oriented individual who enjoys being outside of your comfort zone. You are comfortable in a fast-paced but sensible work environment. You value curiosity and empathy and lead with these values.
Responsibilities
Make daily progress on assigned engineering tasks, such as designing systems, writing specs, writing and pushing code via git, writing release plans for complex changes, rolling out production releases and working with other teams to coordinate system actions
Participate in daily and ad-hoc team meetings to share progress and collaborate
Participate in the team’s on-call schedule to ensure uptime of our production systems
Investigating customer issues that are escalated to the Egress team for triage and resolution
Responding to questions from other teams in the Egress team’s internal, public chat room
Using AI-powered tools and systems as part of your daily workflow to analyze and extend codebases, introspect production systems and datasets, and accelerate problem-solving
Desirable Skills, Knowledge, and Experience
Programming experience in
Go or Rust
and a desire to improve your skills in both.
A solid grasp of networking protocols in Layers 3 and 4 of the OSI Model.
Knowledge of HTTP, TLS, and CDN networks.
Experience in implementing secure and highly-available distributed systems.
Strong ability to debug issues in complex systems.
Strong collaboration and communication skills.
Experience/interest in HTTP networking and VPN technologies.
Experience/interest in network performance monitoring and tuning.
Willingness to adopt and integrate AI tools and systems into your engineering workflow.
Bonus Points
Knowledge of TCP/IP and Internet routing.
Professional systems-level programming experience in Rust.
Experience building tools and APIs.
Experience with monitoring, alerting, and debugging large-scale distributed systems
Experience participating in an on-call rotation.
Experience using AI-assisted development tools (e.g., code completion, codebase analysis, log/data exploration) in a professional setting.
Compensation
● For Portugal based hires: Estimated annual salary is between €66,000 - €91,000.
The final offer will be inclusive of time exemption, in alignment with the applicable law and collective bargaining agreements.
Equity
This role is eligible to participate in Cloudflare’s equity plan.
What Makes Cloudflare Special?
We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.
Project Galileo
: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.
Athenian Project
: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.
1.1.1.1
: We released
1.1.1.1
to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our
privacy commitment
and ensure that no user data is sold to advertisers or used to target consumers.
Sound like something you’d like to be a part of? We’d love to hear from you!
Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs. More details about this will be available at that stage of the interview process.
This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license.
Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual
race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law.
We are an AA/Veterans/Disabled Employer.
Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at
hr@cloudflare.com
or via mail at 101 Townsend St. San Francisco, CA 94107.
Location: San Francisco, CA | New York City, NY | Seattle, WA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role:
We are looking for experienced software engineers to join our Platform organization. We build the foundational primitives that accelerate product development across Anthropic, and own infrastructure and systems that teams depend on to ship reliably and at scale - either internally or by hundreds of thousands of external global users and companies at all stages.
You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You'll partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day.
We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential.
You might be a good fit if you:
Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent
distributed systems, cloud-native products, developer tools, or external developer facing products
Have strong fundamentals in service-oriented architectures, networking, and systems design, ideally having owned both the technical vision and execution of a foundational platform system end to end
Are proficient in Python, Go, Rust, or similar systems languages
Have experience with cloud infrastructure (GCP, AWS, or Azure), container orchestration (Kubernetes), and/or multi-cloud networking
Take full ownership of your work—from design through deployment and operations
Can navigate ambiguity and make sound technical decisions independently, and have ideally operated in 0 to 1 and more mature team or company settings
Take a product-focused approach to platform work and care about building solutions that are robust, scalable, and easy to use
Care about building systems that other engineers love to use
Deadline to apply:
None. Applications will be reviewed on a rolling basis.
Location Preference:
Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$405,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: Remote, Global
Workplace: Remote
ABOUT SUPABASE
Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth.
ABOUT THE ROLE
Auth https://supabase.com/auth, written in Go https://github.com/supabase/auth (server) and with client libraries for TypeScript https://github.com/supabase/supabase-js, SSR https://github.com/supabase/ssr and for other frameworks and technologies, is one of the most popular products in the Supabase stack. We are seeking someone to help us build new and maintain existing Auth features.
WHAT YOU’LL BE RESPONSIBLE FOR
- Designing and implementing secure, scalable authentication features in Go and TypeScript.
- Working across the stack: from server-side protocols to client-side libraries for frameworks like Next.js.
- Owning the performance, reliability, and scalability of the Auth server across Supabase's infrastructure.
- Contributing to the evolution of our Auth architecture, including support for OAuth, OIDC, SAML, and other protocols.
- Planning and executing safe database migrations across a large fleet of Postgres instances.
- Building and improving observability: metrics, tracing, alerting, and dashboards to keep the system healthy at scale.
- Writing and reviewing RFCs as part of our product development process.
- Collaborating with engineers across Supabase to ensure a seamless experience for developers using our tools.
- Supporting the community and responding to developer feedback on GitHub, Discord, and other channels.
YOU MIGHT BE A GOOD FIT IF YOU
- (Required) Have 4+ years of professional experience writing and shipping Go in production.
- (Required) Have 2+ years of professional experience working on an authentication system (implementing protocol support, maintenance at scale).
- (Required) Have strong relational database experience (Postgres or MySQL); Postgres experience is a bonus.
- Have strong knowledge of TypeScript in addition to Go (languages used daily).
- Have strong knowledge of web technology fundamentals (cookies, sessions, JWT, HTTP, browser APIs).
- Have good knowledge of and deep interest in authentication security (passwords, protocols such as OAuth, OIDC or SAML, cryptography fundamentals such as hash functions, signatures and ciphers).
- Have experience working with multiple web frameworks like Next.js (or other SSR alternative in the JavaScript space) and traditional web frameworks like Ruby on Rails, Django, Laravel or equivalent (in any language).
- Have good technical writing skills (RFC process is an important part of making changes to the Auth product).
- Have hands-on experience building and operating services at significant scale.
- Have deep understanding of systems-level concerns: memory management, concurrency patterns, and compute resource optimization in Go.
- Have experience with Kubernetes and AWS (or comparable cloud platform) in a production setting.
- Have solid grasp of observability practices — metrics, distributed tracing, structured logging, and alerting (e.g., Prometheus, Grafana, OpenTelemetry).
- Have experience managing database schema migrations safely at scale.
WHAT WE OFFER
- Fully Remote
We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world.
- ESOP
Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together.
- Tech Allowance
Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work.
- Health Benefits
Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us.
- Annual Off-Sites
Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year.
- Flexible Work
We operate asynchronously and trust you to manage your own time. You know what needs to be done and when.
- Professional Development
Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth.
ABOUT THE TEAM
Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love.
- ~400 team members
- 60+ countries
- 20+ languages spoken
- Over $1B raised (including our $500M Series F)
- 540,000+ community members
We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.
Location: Europe
Workplace: Remote
Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US.
As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations.
Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow.
We’re looking for a Principal Engineer to join the ML Platform team at Synthesia.
Our team builds and operates the systems that allow researchers and product teams to train, serve, and deploy generative models reliably and efficiently. This includes research infrastructure, production serving systems, internal tooling, and the platform interfaces that connect them. A growing part of our mission is making these systems more automation-friendly and agent-oriented, so that workflows can increasingly be operated through reliable tooling rather than manual effort.
We’re looking for a strong generalist with a systems mindset:
- someone who is comfortable working across infrastructure, backend systems, and tooling, and who has seen ML systems in practice.
- this is not a pure ML Engineer role. We’re especially interested in people who think deeply about reliability, scalability, performance, and resource efficiency in complex production environments.
This is a hands-on IC role with significant ownership. You’ll help shape how our ML platform evolves as we scale the number of models, workloads, tools and teams relying on it.
WHAT YOU’LL DO
- Design and improve the platform systems that support model training, evaluation, and production serving.
- Build infrastructure and tooling that make ML workloads more reliable, scalable, and cost-efficient.
- Develop internal tools and workflows that are easy to operate both by humans and by agents.
- Work on the architecture behind how models are deployed, served, and operated across research and product environments.
- Improve how we schedule, monitor, and debug workloads running on GPUs and cloud infrastructure.
- Develop internal tools and abstractions and agentic systems that reduce operational overhead for researchers and engineers.
- Drive improvements across observability, automation, reliability, and developer experience.
- Collaborate closely with researchers and product engineers to understand pain points and turn them into robust platform capabilities.
- Contribute to technical direction and make pragmatic architectural tradeoffs as the platform grows.
YOU’LL THRIVE IN THIS ROLE IF YOU HAVE
- Strong experience building or operating production systems with a focus on reliability, scalability, and maintainability.
- A systems mindset: you naturally think in terms of bottlenecks, failure modes, interfaces, resource usage, and long-term operability.
- Solid hands-on experience with cloud infrastructure, Linux, and infrastructure automation.
- Experience with Kubernetes and operating distributed workloads in production.
- Strong coding skills, ideally in Python or similar languages used for backend systems and tooling.
- Strong judgment around where automation adds leverage, and where human control and reliability matter most.
- Experience building internal platforms, developer tooling, or infrastructure abstractions used by other engineers.
- Comfort working in ambiguous environments and taking ownership of open-ended technical problems.
- A pragmatic approach: you care about solving the right problem well, not over-engineering.
PARTICULARLY RELEVANT EXPERIENCE
- Operating ML infrastructure or model serving systems in production.
- Supporting research or data-intensive workloads.
- Working with GPU-based systems or other performance-sensitive infrastructure.
- Experience with observability and debugging in distributed systems.
- Familiarity with Terraform, Datadog, GitHub Actions, or similar tools.
BONUS POINTS FOR
- Experience building agentic or LLM-powered internal tools.
- Experience with workflow orchestration systems such as Temporal.
- Experience working at the boundary between research and production engineering.
- Familiarity with performance optimization, scheduling, or resource allocation problems.
- Experience building lightweight product or developer-facing tools.
Location: Espoo; Berlin
Workplace: Hybrid
- Title: Staff Platform Engineer
- Department: Platform & Release Engineering
- Location: Espoo, Finland / Berlin, Germany
- Reports to: Infrastructure Engineering Lead
- Employment type: Permanent
- Workplace model: Hybrid
- Employment is subject to applicable security screening (incl. SUPO)
WHY THIS ROLE MATTERS:
As a Senior / Staff Platform Engineer, you’ll own and evolve the foundations that all services rely on, leading the design and operation of a secure, scalable Kubernetes platform across cloud and on-prem environments so product teams can ship faster with less friction and stronger reliability at scale.
WHO WE ARE
ICEYE delivers space-based intelligence, surveillance, and reconnaissance (ISR) capabilities to governments and allied nations. This includes sovereign and turnkey ISR missions leveraging ICEYE’s world-leading synthetic aperture radar (SAR) satellite technology, as well as access to data from the world’s largest SAR satellite constellation. These capabilities enable partners to detect and respond to critical changes anywhere on Earth with unprecedented speed and accuracy, day or night and in any weather, supported by ultra high-resolution imagery and high-frequency revisits.
As a trusted partner for defense, intelligence, security, and maritime domain awareness, ICEYE’s near real-time data creates a tactical advantage for mission-critical operations. Designed for dual use, the platform also serves civil protection and commercial users for natural-catastrophe intelligence, insurance, maritime monitoring including oil-spill detection, and finance, contributing to global security and community resilience.
ICEYE is headquartered in Finland and operates globally across Europe, North America, the Middle East, and Asia-Pacific. We have more than 900 employees, united by a shared vision: improving life on Earth by becoming the global source of truth in Earth Observation.
YOUR DAY-TO-DAY RESPONSIBILITIES
- Design, operate, and continuously improve a secure, scalable, and resilient Kubernetes platform across cloud and on-prem environments
- Build and maintain standardized platform capabilities such as ingress, service mesh, secrets management, and lifecycle automation
- Develop reusable infrastructure patterns and Terraform modules for AWS and on-prem platforms to enable fast, auditable provisioning
- Strengthen observability through clear metrics, logs, traces, dashboards, and actionable alerting that support effective operational decisions
- Reduce platform friction for product teams by providing architectural guidance, platform standards, and hands-on enablement
- Automate platform lifecycle management including bootstrap, upgrades, scaling, and operational maintenance to reduce manual effort and risk
- Drive technical direction and sound architectural choices across platform engineering with pragmatic trade-offs between reliability, security, speed, and maintainability
- Help raise engineering maturity by mentoring others and shaping shared engineering standards across teams
WHAT WE’RE LOOKING FOR
MUST HAVES:
- 8+ years of experience in Platform Engineering, SRE, DevOps, or infrastructure roles operating production-critical services at scale
- Deep hands-on expertise with Kubernetes, including cluster architecture, upgrades, control plane operations, networking, ingress, storage, security, and lifecycle management
- Strong understanding of AWS fundamentals, including networking, IAM, compute, storage, and security patterns
- Strong experience with Terraform and infrastructure as code, including reusable modules, abstractions, and scalable provisioning patterns
- Strong practical observability experience, including SLO and SLI design, instrumentation, dashboarding, alert strategy, and production performance analysis
- Proficiency in at least one backend language such as Python or Go for automation, tooling, and internal platform capabilities
- Experience providing technical leadership through platform standards, architectural guidance, and hands-on enablement
- Ability to operate effectively in complex environments and make pragmatic technical decisions across reliability, security, speed, and maintainability
NICE TO HAVES:
- Experience with Rancher, Istio, External Secrets, Vault, and software supply-chain hardening practices
- Experience operating Kubernetes in restricted, disconnected, or air-gapped environments
- Experience with hybrid platforms spanning AWS and on-prem environments such as vSphere or VxRail
APPLICATION PROCESS
- Talent Attraction Introduction
- Hiring Manager Alignment
- Task Assignment
- Technical Interview
- Director Interview
WORKING AT ICEYE
At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win.
HOW WE WORK (OUR VALUES)
Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way.
- Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the why behind decisions.
- See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others.
- Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions.
- Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift.
- Have fun: What we do matters and it should be enjoyable. Celebrate progress, take pride in results, and share the wins.
BENEFITS
Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process.
OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION
We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table.
We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us and we will do our best to help.
Apply now to start your ICEYE journey and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.
Location: Switzerland
Workplace: Remote
About Inworld
Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads.
Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production.
We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA.
Who We're Looking For
A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.
Experience We Find Useful
You don't need all of this. But you need enough to make a case.
- Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM.
- Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding.
- High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs.
- Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections.
- Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups.
- Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production.
- Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems.
- Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams.
Who Thrives Here
- You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go.
- You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations.
- You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem.
- You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make.
What Working Here Is Like
We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.
Location & Employment
- Location: remote within Switzerland
- Employment type: Full-time, permanent employment
- Hiring model: Employment via Employer of Record (EOR)
Candidates must already have the legal right to work in Switzerland, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements.
Inworld Jobs Privacy https://inworld.ai/jobs-privacy
Location: UK
Workplace: Remote
About Inworld
Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads.
Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production.
We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA.
Who We're Looking For
A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.
Experience We Find Useful
You don't need all of this. But you need enough to make a case.
- Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM.
- Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding.
- High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs.
- Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections.
- Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups.
- Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production.
- Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems.
Who Thrives Here
- You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go.
- You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations.
- You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem.
- You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make.
What Working Here Is Like
We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.
The base salary range for this full-time position is £140,000 – £200,000. In addition to base pay, total compensation includes equity and benefits. Within the range, individual pay is determined by work location, level, and additional factors, including competencies, experience, and business needs. The base pay range is subject to change and may be modified in the future.
Candidates must already have the legal right to work in the United Kingdom, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements.
Inworld Jobs Privacy https://inworld.ai/jobs-privacy
Location: Serbia
Workplace: Remote
About Inworld
Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads.
Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production.
We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA.
Who We're Looking For
A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.
Experience We Find Useful
You don't need all of this. But you need enough to make a case.
- Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM.
- Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding.
- High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs.
- Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections.
- Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups.
- Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production.
- Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems.
- Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams.
Who Thrives Here
- You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go.
- You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations.
- You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem.
- You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make.
What Working Here Is Like
We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.
For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements.
Inworld Jobs Privacy https://inworld.ai/jobs-privacy
Location: Germany
Workplace: Remote
About Inworld
Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads.
Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production.
We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA.
Who We're Looking For
A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.
Experience We Find Useful
You don't need all of this. But you need enough to make a case.
- Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM.
- Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding.
- High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs.
- Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections.
- Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups.
- Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production.
- Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems.
- Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams.
Who Thrives Here
- You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go.
- You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations.
- You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem.
- You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make.
What Working Here Is Like
We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.
For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements.
Inworld Jobs Privacy https://inworld.ai/jobs-privacy
London
London
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
Настройте подбор, и подходящие вакансии будут приходить в Telegram.
ГибридseniorTbilisi, Georgia; Limassol, Cyprus; Relocation support and private health insurance
seniorAmsterdam, Netherlands; Germany; London, United Kingdom; Poland
УдалённоseniorIndia
Amsterdam, Netherlands; Tel Aviv, Israel
seniorГеография найма не уточнена
San Francisco, CA | New York City, NY | Seattle, WA; Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team
УдалённоМожно работать из любой страны
УдалённоEurope
ГибридEspoo; Berlin
УдалённоseniorПротиворечивые условия: For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S; visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements
УдалённоseniorПротиворечивые условия: For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S; visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements
УдалённоleadПротиворечивые условия: For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S; visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements
УдалённоleadПротиворечивые условия: For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S; visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements
Автоотклики