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Location: Global, EU We are the creators of a new fintech era! Our mission is to change this world by making blockchain accessible to everyone in everyday life. WhiteBIT is a global team of over 1,200 professionals united by one mission — to shape the new world order in the Web3 era. Each of our employees is fully engaged in this transformative journey. We work on our blockchain platform, providing maximum transparency and security for more than 8 million users worldwide. Our breakthrough solutions, incredible speed of adaptation to market challenges, and technological superiority are the strengths that take us beyond ordinary companies. Our official partners include the National Football Team of Ukraine, FC Barcelona, Lifecell, FACEIT and VISA. The future of Web3 starts with you: join us as a DevOps Engineer with Big Data Skills! Requirements We're looking for a DevOps engineer with 4+ years of hands-on experience, at least 2 of them spent building and running data or analytics infrastructure. You've designed systems that move, store, and serve data at scale. Warehouse maintenance is part of your daily routine, and writing Python, Bash, or SQL scripts is second nature. You treat data security as a core responsibility: you protect confidentiality, enforce zero-trust, least-privilege access, and automate everything you touch. Solid IaC skills are a must. IaC & CI/CD: Production experience with Terraform, Ansible, and Helm, plus CI/CD systems (GitLab CI, GitHub Actions, Jenkins, or ArgoCD). We expect you to design pipelines, not just use them. Containerization: Working knowledge of Docker and Kubernetes, including running data workloads on it (like Spark on Kubernetes, stateful services, operators). Cloud: Solid experience with AWS (S3, EC2, EMR, Redshift, Glue, IAM) or an equivalent cloud provider. Linux & Networking: Solid Linux administration skills and foundational networking knowledge relevant to distributed systems. Analytical Databases: Hands-on operation of ClickHouse and/or the Hadoop ecosystem (HDFS, Hive, YARN), including cluster setup, tuning, and scaling. Data Warehouses: Practical experience with Snowflake or Redshift, covering warehouse sizing, workload management, performance tuning, and cost control. Large Databases: Experience administering databases at terabyte scale: replication, backup and restore strategies, partitioning, and migrations with minimal downtime. SQL & Scripting: Strong SQL skills, including reading execution plans and optimizing heavy queries. Confident in Python and Bash for automation, data parsing, and investigation. Data Lakes & Object Storage: Working knowledge of S3-compatible storage, columnar formats, partitioning strategies, and data lifecycle management. Orchestration & Streaming: Familiarity with Airflow (or similar orchestrators) and Kafka, and how they fit into data pipelines. Extra Credit / Big Pluses Experience with Tableau, Power BI, Looker, Superset, or similar BI tools, including administration, performance tuning, and data source design. Hands-on experience with dbt and analytics engineering practices. Experience with open table formats (Apache Iceberg, Delta Lake, Hudi) and query engines like Trino/Presto or Athena. FinOps experience in data platforms: managing Snowflake credits, Redshift clusters, and storage costs at scale. Spark performance tuning and job optimization. Change data capture (CDC) with Debezium or similar tools. Data quality tooling (Great Expectations, Soda) integrated into CI/CD. Golang or Rust tooling experience. Knowledge of data governance and compliance (GDPR, data retention, PII handling). Understanding of business processes in the FinTech/Banking/Crypto sector. Responsibilities Infrastructure Ownership: Own the infrastructure behind our data and analytics platform, from provisioning to daily operations. Keep it reliable, scalable, and cost-efficient as data volumes grow. Infrastructure as Code: Provision and configure all data infrastructure with Terraform, Ansible, and Helm. CI/CD Pipelines: Build and maintain delivery pipelines for both infrastructure and data code (ETL jobs, Airflow DAGs, dbt models, schema migrations), with automated testing, safe rollouts, and fast rollback. Database & Warehouse Operations: Maintain ClickHouse, Snowflake, Redshift, and вPostgreSQL at multi-terabyte scale, handling replication, backups, upgrades, capacity planning, and disaster recovery. Data Lake Storage: Manage S3-compatible data lake storage, including partitioning, file formats, and lifecycle policies. Automation & Script Optimization: Refactor and automate Python, Bash, and SQL scripts to cut runtimes and eliminate manual work. Performance & Cost: Right-size clusters and warehouses, tune heavy queries, and keep compute and storage spend under control. Monitoring & Alerting: Cover data infrastructure with metrics, logs, and alerts for cluster health, pipeline SLAs, and job failures. Security & Access Control: Enforce least-privilege access, secrets management, encryption, and auditability for sensitive data. BI Infrastructure: Support the infrastructure behind Tableau or similar BI tools. Big Data Platforms: Deploy, tune, and troubleshoot Hadoop, Spark, and Kafka clusters in production. Collaboration: Work with data engineers, analysts, and developers to turn their workloads into solid infrastructure decisions. Security & Access Control: Implement role-based access, secrets management, encryption at rest and in transit, and auditability for sensitive datasets in line with regulatory requirements. Working terms Immerse yourself in Crypto & Web3: Master cutting-edge technologies and become an expert in the most innovative industry. Work with the Fintech of the Future: Develop your skills in digital finance and shape the global market. Take Your Professionalism to the Next Level: Gain unique experience and be part of global transformations. Drive Innovations: Influence the industry and contribute to groundbreaking solutions. Join a Strong Team: Collaborate with top experts worldwide and grow alongside the best. Work-Life Balance & Well-being: Modern equipment. Comfortable working conditions, and an inspiring environment to help you thrive. 24 calendar days of paid leave. Additional days off for national holidays. With us, you’ll dive into the world of unique blockchain technologies, reshape the crypto landscape, and become an innovator in your field. If you’re ready to take on challenges and join our dynamic team, apply now and start a new chapter in your career! Let’s Build the Future Together! WhiteBIT offers all candidates an equal opportunity to join the team. All hiring decisions are made without regard to race, national origin, gender identity or sexual orientation, age, religion, disability, medical condition, marital status, familial status, veteran status, or any other legally protected characteristic of an individual. Your privacy matters to us. You can learn more about how we handle your personal data with regard to your application in our Candidate Privacy Notice .

Location: Serbia; Spain Social Discovery Group (SDG) is a group of social discovery companies. SDG solves the problems of loneliness, isolation, and disconnection - transforming virtual intimacy into the new normal. SDG’s products redefine the way people interact and connect with one another. Our portfolio includes social entertainment platforms designed to connect people online across different cultures and regions of the world. We bring together a team of like-minded people and IT professionals who specialize in creating and developing globally impactful social discovery products. Our international team of digital nomads works remotely from all over the world. We’re proud to be a two-time “Great Place to Work” winner (USA & Japan, 2024–2025) and a Top-5 Company for Work-From-Anywhere Jobs (FlexJobs, 2025). We are looking for Lead ML Engineer -LLM Inference & NLP . Your main tasks will be: Speed up and scale LLM inference in production: SGLang, KV and prefix caching, batching, quantization, speculative decoding Run distributed inference for very large models (up to 1T+ parameters) across multi-GPU and multi-node setups Benchmark new GPU servers and hardware, bring them into production and adapt our serving code to them Lead the NLP and CV teams technically: review experiments, set direction, and step in early when something is heading the wrong way Train and fine-tune the language models, and improve the agent harnesses and chat algorithm that run on them Track cutting-edge research and open-source work in inference and post-training, and turn it into the ML roadmap Collaborate closely with the validation, content, and dataset preparation teams to design experiments and measure model quality We expect from you: Deep hands-on experience optimizing LLM inference in production with SGLang, vLLM, or TensorRT-LLM Experience with distributed inference or training of large models: MoE, tensor/expert/pipeline parallelism, multi-node GPU clusters Strong understanding of what makes inference fast: KV cache, attention kernels, batching, quantization, GPU profiling Experience training and fine-tuning LLMs, including post-training (RLHF, DPO, or similar) Proven technical leadership: you've guided engineers through reviews, mentoring and technical decisions while still writing code yourself Proficiency with PyTorch, transformers, and related libraries Experience at AI-focused startups or companies (Character AI, OpenAI, and similar is a strong plus) Backend engineering experience (Python, Go, C#) and knowledge of scalable deployment systems is a significant advantage Advanced English or Russian Nice to have: CUDA or Triton kernel development A computer vision background. We also welcome strong CV leads who have accelerated large generative image or video models Experience with multimodal LLMs First-author papers or notable open-source work, e.g. contributions to SGLang, vLLM, or post-training libraries A degree in CS, math, or physics from a strong program (MSc or PhD) What do we offer: REMOTE OPPORTUNITY to work full-time; The initial pay level or pay range for this role will be shared with candidates during the recruitment process and before the commencement of employment; Vacation 28 calendar days per year; 7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave; Bonuses up to $5000 for recommending successful applicants for positions in the company; 50% payment for professional training, international conferences, and meetings; Corporate discount for English lessons; ​ Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); ​ Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years; Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now!

Location: New York City, NY | Seattle, WA; 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 Anthropic is looking for a Staff+ Software Engineer to work on the vector search infrastructure behind Claude. Retrieval is how Claude learns about the world. Web search across claude.ai, the API and agentic surfaces, memory across conversations, and the reinforcement learning workloads that train our next models all depend on fast, cheap, high-recall nearest-neighbor search over billions of vectors. You'll join a small team responsible for the vector database layer that serves Claude's retrieval workloads: its architecture, performance, scalability and cost. This is a foundational role. The team is small, core architectural decisions are still open, and the engineers who join now will shape how the system evolves. The role sits in our Databases organization and works day to day with the Search Platform team, which owns web search indexing, retrieval and serving, and the Memory & Search team, which owns search and memory inside claude.ai. We're looking for someone who has built vector or search systems that ran in production, at scale, with real users and a real on-call. You'll be hands-on in the code, and you'll also be the person deciding how the pieces fit together. Key responsibilities Own the core of Anthropic's vector database layer: index structures, storage layout, query execution and the serving layer Own production readiness - benchmarking against exact search, capacity planning, onboarding new workloads, and the operational tooling to run it at scale Drive the recall, latency and cost trade-offs - quantization, filtered search, index build and refresh strategy, and how compute and storage are separated and scaled Scale throughput by an order of magnitude as research and training demand grows, and work out whether the bottleneck is architecture, hardware or engineering bandwidth Extend the retrieval stack toward hybrid retrieval - lexical search and fused ranking alongside vector search Set the evaluation methodology for the system -  recall targets, latency objectives, cost per query, and the regression detection that keeps them honest Set technical direction for a growing team - lead design reviews, make architectural decisions others build on, and mentor the engineers joining the effort Share the on-call for the systems you own Minimum qualifications Direct experience building a vector database or approximate nearest-neighbor search system that ran in production at scale Deep knowledge of ANN index structures (graph-based, clustering-based or disk-resident approaches), vector quantization and filtered search Experience with search relevance and ranking Strong systems programming skills in a language such as Rust, C++ or Go, including performance-critical and memory-intensive code Experience designing and operating large-scale distributed storage or serving systems with strict latency and reliability requirements A track record of independently scoping and delivering ambiguous, multi-quarter technical projects Strong written and verbal communication, with experience driving alignment across teams with different priorities Interest in AI safety and Anthropic's mission Preferred qualifications Experience with object-storage-backed or disaggregated compute and storage database designs Experience building or operating full-text search engines (inverted indexes, BM25) or hybrid retrieval systems Familiarity with embedding models and the retrieval demands of LLM training and inference Experience using GPUs or other accelerators for index build or search Prior experience as a technical lead on a database or search infrastructure 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: $320,000 — $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. 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 - United Kingdom NeoCloud BD Pursuit Specialist / Account Executive Backblaze (Nasdaq: BLZE) | Reports to the Head of NeoCloud Sales How We Got Here We started by building storage servers from scratch in a Palo Alto apartment to save 90% on hardware. Turns out hard constraints make for pretty good engineering. That discipline forged a platform that performs as well or better than competitors, scales to multi-exabyte workloads, and costs a fraction of what AWS or Google charge. AI infrastructure runs on data. Storage gets hard at scale. We've been breaking, rebuilding, and improving that storage layer for 20 years. Today, the world's leading AI infrastructure providers, neoclouds, and data-intensive businesses run on Backblaze. Our platform includes: B2 Overdrive - high-throughput object storage engineered for AI infrastructure, GPU workloads, and massive-scale data pipelines B2 Neo - white-label enterprise cloud storage powering neocloud platforms for AI, HPC, and media B2 Cloud Storage - S3-compatible object storage with predictable pricing, free egress, and no lock-in Computer Backup - automatic, continuous endpoint backup for Macs and PCs 500,000+ customers. 175 countries. Nasdaq: BLZE. backblaze.com The Role NeoClouds are GPU-rich, AI-native infrastructure providers, and they need fast, affordable, S3-compatible storage at scale. Backblaze is the high-performance capacity storage layer for AI. You will win these accounts. This is a new-logo role. You will own a named set of NeoClouds from the top 80 worldwide and pursue them from first meeting to signed contract. This is not an inbound role. If you want a defined territory and a queue of warm leads, it isn't the right fit. If your instinct is to pick an account, find the engineer who feels the storage cost first, and work up to the CXO, keep reading. What You Will Do Pursue named accounts. Build a pursuit plan for each account. Map the buying group from infrastructure engineers to the CXO, and build relationships across it. Run discovery. Learn how each NeoCloud runs its stack, where storage costs and performance limit it, and how Backblaze fits. Work with the Sales Engineer and Field CTO on technical validation and proof-of-concept testing. Choose the route. Your motion is Sell-To. Decide with your manager when an account also calls for Sell-With, which Strategic Partnerships runs with the Head of NeoCloud Sales. When a partner such as NVIDIA, Super Micro, Weka, VAST, or AMD helps win the account, bring in Strategic Partnerships. Shape the deal. Work with your manager and legal on multi-year commitments, SLAs, and revenue share when Backblaze runs behind a NeoCloud's storage service. Sell inside Backblaze. Pull Cloud Operations and Engineering into the integration early. Their time is as scarce as your buyer's, and you will earn it. Line up executive sponsors. Secure a Backblaze executive sponsor and a customer executive sponsor on every priority account. Hand off and expand. Bring in the strategic account manager in Customer Success as customers go live, and stay in the account as it grows. Keep the forecast honest. Maintain accurate pipeline, next steps, and close dates in the CRM. What We Are Looking For Infrastructure sales expertise , with a record of closing complex, multi-year deals in storage, cloud, compute, networking, or data center infrastructure Technical fluency. You run most technical conversations with infrastructure engineers and architects about GPU clusters, networking, and storage yourself, and earn their trust. The Sales Engineer owns deeper validation and proofs of concept Executive presence. You have built VP, SVP, and CTO relationships and can lead those meetings Hunter drive. You open doors in accounts that do not know you yet, and you stay with a long pursuit Seller of record. You have carried a quota and closed deals with your name on them Deal structure experience. You have negotiated SLA, IP, and revenue-share terms on deals you closed, not just understood them Team play. You work well with sales engineers, partner teams, and operations teams to land one account Also True of the Right Person Existing relationships with NeoCloud technical or executive leaders Experience with OEM, ISV, or co-sell motions Familiarity with S3-compatible object storage, data egress economics, and AI/ML data pipelines This Is Not the Role for You If You want a defined territory or an inbound queue rather than named accounts you have to open You prefer a short sales cycle to a long pursuit You hand technical questions to someone else and wait for the answer You want to bring a SaaS motion here unchanged You work accounts alone rather than with sales engineering, partners, and operations How We Will Interview We will ask you to walk us through a pursuit you ran from first meeting to signed contract, including a long one that stalled and how you kept it moving. We will ask how you earned an infrastructure engineer's trust. We will ask for your own view of how you would approach this role. You will hold cross-functional conversations with the Sales Engineer and the Field CTO, because you will pursue accounts with them. And you will go through a panel, so we can see how you work. At Backblaze, we value being fair and good to our customers, partners, and employees. Diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We are proud to be an Equal Opportunity Employer.

Location: Remote - US NeoCloud BD Pursuit Specialist / Account Executive Backblaze (Nasdaq: BLZE) | Reports to the Head of NeoCloud Sales Salary range: $171,000 - $192,000, plus variable pay and RSUs. Target OTE $285,000 - $320,000, 60:40 base to variable. How We Got Here We started by building storage servers from scratch in a Palo Alto apartment to save 90% on hardware. Turns out hard constraints make for pretty good engineering. That discipline forged a platform that performs as well or better than competitors, scales to multi-exabyte workloads, and costs a fraction of what AWS or Google charge. AI infrastructure runs on data. Storage gets hard at scale. We've been breaking, rebuilding, and improving that storage layer for 20 years. Today, the world's leading AI infrastructure providers, neoclouds, and data-intensive businesses run on Backblaze. Our platform includes: B2 Overdrive - high-throughput object storage engineered for AI infrastructure, GPU workloads, and massive-scale data pipelines B2 Neo - white-label enterprise cloud storage powering neocloud platforms for AI, HPC, and media B2 Cloud Storage - S3-compatible object storage with predictable pricing, free egress, and no lock-in Computer Backup - automatic, continuous endpoint backup for Macs and PCs 500,000+ customers. 175 countries. Nasdaq: BLZE. backblaze.com The Role NeoClouds are GPU-rich, AI-native infrastructure providers, and they need fast, affordable, S3-compatible storage at scale. Backblaze is the high-performance capacity storage layer for AI. You will win these accounts. This is a new-logo role. You will own a named set of NeoClouds from the top 80 worldwide and pursue them from first meeting to signed contract. This is not an inbound role. If you want a defined territory and a queue of warm leads, it isn't the right fit. If your instinct is to pick an account, find the engineer who feels the storage cost first, and work up to the CXO, keep reading. What You Will Do Pursue named accounts. Build a pursuit plan for each account. Map the buying group from infrastructure engineers to the CXO, and build relationships across it. Run discovery. Learn how each NeoCloud runs its stack, where storage costs and performance limit it, and how Backblaze fits. Work with the Sales Engineer and Field CTO on technical validation and proof-of-concept testing. Choose the route. Your motion is Sell-To. Decide with your manager when an account also calls for Sell-With, which Strategic Partnerships runs with the Head of NeoCloud Sales. When a partner such as NVIDIA, Super Micro, Weka, VAST, or AMD helps win the account, bring in Strategic Partnerships. Shape the deal. Work with your manager and legal on multi-year commitments, SLAs, and revenue share when Backblaze runs behind a NeoCloud's storage service. Sell inside Backblaze. Pull Cloud Operations and Engineering into the integration early. Their time is as scarce as your buyer's, and you will earn it. Line up executive sponsors. Secure a Backblaze executive sponsor and a customer executive sponsor on every priority account. Hand off and expand. Bring in the strategic account manager in Customer Success as customers go live, and stay in the account as it grows. Keep the forecast honest. Maintain accurate pipeline, next steps, and close dates in the CRM. What We Are Looking For Infrastructure sales expertise , with a record of closing complex, multi-year deals in storage, cloud, compute, networking, or data center infrastructure Technical fluency. You run most technical conversations with infrastructure engineers and architects about GPU clusters, networking, and storage yourself, and earn their trust. The Sales Engineer owns deeper validation and proofs of concept Executive presence. You have built VP, SVP, and CTO relationships and can lead those meetings Hunter drive. You open doors in accounts that do not know you yet, and you stay with a long pursuit Seller of record. You have carried a quota and closed deals with your name on them Deal structure experience. You have negotiated SLA, IP, and revenue-share terms on deals you closed, not just understood them Team play. You work well with sales engineers, partner teams, and operations teams to land one account Also True of the Right Person Existing relationships with NeoCloud technical or executive leaders Experience with OEM, ISV, or co-sell motions Familiarity with S3-compatible object storage, data egress economics, and AI/ML data pipelines This Is Not the Role for You If You want a defined territory or an inbound queue rather than named accounts you have to open You prefer a short sales cycle to a long pursuit You hand technical questions to someone else and wait for the answer You want to bring a SaaS motion here unchanged You work accounts alone rather than with sales engineering, partners, and operations How We Will Interview We will ask you to walk us through a pursuit you ran from first meeting to signed contract, including a long one that stalled and how you kept it moving. We will ask how you earned an infrastructure engineer's trust. We will ask for your own view of how you would approach this role. You will hold cross-functional conversations with the Sales Engineer and the Field CTO, because you will pursue accounts with them. And you will go through a panel, so we can see how you work. What We Offer Competitive compensation and equity package Full benefits including medical, dental, vision, and 401(k) with matching RSU grants for full-time employees ESPP program Flexible vacation policy Maternity & paternity leave MacBook to use for work, plus a generous stipend to personalize your workstation Childcare bonus (human children only) Fertility treatment and support Learning & development program Commuter benefits A collaborative and transparent culture that supports a healthy work-life balance Pay Transparency and Equal Opportunity To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. Final offer amounts are determined by multiple factors including candidate location, skills, depth of work experience, and relevant licenses/credentials. Compensation for this role is $171,000 - $192,000 , plus variable pay and RSUs. Target OTE $285,000 - $320,000 , 60:40 base to variable. At Backblaze, we value being fair and good to our customers, partners, and employees. Diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We are proud to be an Equal Opportunity Employer.

Location: Paris; London Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE JOB Mistral AI is seeking Applied Scientists and Research Engineers focused on robotics. You will design, train, and deploy SOTA robotics models (VLM, VLA models for navigation and manipulation) and apply them to diverse use cases. You'll work cross-functionally with internal and external science, engineering, and product teams to deliver high-impact AI solutions. WHAT YOU WILL DO - Run pre-training, post-training and deploy state of the art models on large clusters. - Generate and curate datasets (image-text, video-text), and build evaluators/benchmarks for perception, navigation and manipulation tasks. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. ABOUT YOU - Fluent in English with excellent communication skills. - Expert with PyTorch or JAX. - Experience with Vision Language Models (VLM), Vision-Language-Action (VLA) models, perception, navigation and manipulation, simulation tools (e.g. Isaac SIM). - Clean, readable, high-performance Python code. - Doesn't need roadmaps. Ships. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. NICE TO HAVE - PhD / Master in a relevant field (Robotics, Machine Learning). - Research experience in robotics navigation, perception, manipulation. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Georgia; Ukraine; Poland; Brazil; Argentina; Colombia Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are looking for a Senior Software Engineer (Elasticsearch, Scala) to join a team powering food search and logging for one of the world’s leading health and nutrition platforms. You’ll contribute directly to the systems that drive search — backend services, search infrastructure, and experimentation — with a focus on improving core metrics: conversion rates, time to log, query abandonment, and result relevance. WHAT YOU’LL DO - Contribute to, build, and maintain backend services that drive the food search experience, integrating with systems across the broader engineering organization. - Perform search performance tuning end-to-end — data design, indexing, query evaluation, and iterative improvement within Elasticsearch. - Assist in the evaluation and implementation of search and data technologies that improve result quality and user experience. - Collaborate closely with senior search engineers, product management, and leadership on solution discovery, experiment planning, and delivery. - Contribute to the development of tools, processes, and metrics for measuring and monitoring search quality. REQUIRED SKILLS & EXPERIENCE Elasticsearch - Demonstrated experience with performance tuning, query analysis, and relevance optimization in Elasticsearch at scale. - Strong understanding of index design, mapping strategies, cluster management, and scoring/ranking mechanics. - Familiarity with high availability, disaster recovery, and operational monitoring for Elasticsearch clusters. - Ability to deploy new indexes or clusters as needed for load balancing or experimentation. - Ability to translate product specifications into technical requirements and deploy ranking and relevance experiments with clearly defined success criteria and metrics. Scala - Strong experience writing, shipping, and maintaining Scala services in production. - Comfortable working across a stack that also includes SQL and Python — Scala is the primary language for this engagement. Agentic development - Active user of AI development tools such as Claude Code, Cursor, or comparable AI-powered coding environments — shipping production code with them, not just using autocomplete. - Familiarity with agentic coding patterns and workflows — code generation, refactoring, debugging, and test authoring. - Able to articulate how AI tooling fits into their development process and where human judgment remains critical. Engineering fundamentals - First-hand experience building, scaling, and supporting large-scale data infrastructure systems in production. - Strong understanding of database design, data architecture, and performance tuning across multiple data stores — MySQL, MongoDB, DynamoDB, Redis, or similar. - Experience with high-volume messaging systems such as Kafka. - Familiarity with AWS, GCP, or other cloud platforms. - Strong peer code review practices. PREFERRED QUALIFICATIONS - Experience leveraging AI workflows for meaningful development acceleration beyond autocomplete — code generation, refactoring, debugging, and test authoring at scale. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: 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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. 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: $320,000 — $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. 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: New York City, NY 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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. 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: $320,000 — $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. 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: Lisbon, Portugal; Madrid, Spain; Prague, Czechia CloudLinux is a global remote-first company. We are driven by our principles: do the right thing, employees first, we are remote first, and we deliver high-volume, low-cost Linux infrastructure and security products that help companies to increase the efficiency of their operations. Every person on our team supports each other and does what we can to ensure we all are successful. Check out our website for more information: cloudlinux.com We are currently hiring a Staff Security Engineer within the Imunify360 product. Imunify360 is CloudLinux's security suite for Linux web servers. It protects hundreds of thousands of hosting servers and the websites running on them, so it sees most large-scale web attacks early — often in the first hours. Check out our website for more information: https://imunify360.com/ Role Mission & Scope At Imunify360, protecting customers from evolving cyber threats requires close collaboration between security research, engineering, and other teams. Responding to complex attack campaigns involves more than identifying threats — it requires understanding attack techniques, developing effective detection and mitigation strategies, and ensuring customers are protected. As a Staff Security Engineer , you'll take end-to-end technical ownership of complex security challenges, from initial threat discovery and analysis to detection, mitigation, and post-incident review. This is a hands-on technical leadership role focused on practical security engineering rather than SOC monitoring, compliance, or purely theoretical research. You'll analyze malware and exploit code, develop detection and mitigation tools, anticipate emerging attack techniques, and ensure security findings translate into production-ready detections, mitigations, and fixes. You'll work closely with engineering, security research, support, external partners, and the broader security community to coordinate responses and drive continuous improvements in our security capabilities. As an individual contributor , you won't have direct reports or people management responsibilities. All security research and testing are conducted within authorized boundaries, with clearly defined scope and responsible disclosure practices. Your mission is to strengthen Imunify360's ability to detect, prevent, and respond to emerging threats, delivering measurable security improvements that protect customers at scale. What you will own Malware and campaign mitigation Lead response to large-scale exploitation and malware campaigns: triage, root cause, and mitigation across every protection layer of the product. Reverse-engineer malware and exploits targeting Linux servers and web applications. Track campaigns over time, not just individual samples: cluster indicators, connect activity to known actors and toolkits, anticipate the next variant. Define and run measurable outcomes per campaign: time to detect, time to protect, cleanup effectiveness, reinfection rate. Security response coordination Own the security incident and response process, both for threats against our customers and for vulnerabilities in our own product: severity model, runbooks, communication, escalation. Coordinate with external parties — software vendors, partners, CERTs/CSIRTs, abuse desks, other security vendors. Drive responsible disclosure where we find vulnerabilities. Be the technical voice in security advisories and partner briefings, together with Product and Support. Triage external vulnerability reports. Offensive security on our own product Red-team our product and infrastructure. Assume a capable attacker who already has a foothold. Threat-model new features before they ship; own the security review gate for high-risk changes. Turn findings into fixes with the owning teams, not just reports. Detection engineering and tooling Raise the quality bar of detections: false-positive budgets, test corpora, staged rollout with measurement gates and fast rollback. Build and automate the analysis pipeline: dynamic analysis, honeypots, telemetry-driven hunting, ML-assisted triage where it measurably helps. Write production code for these tools; expect 30–50% of your time to be hands-on building. Turn telemetry into intelligence: emerging exploits, attacker infrastructure, trends — shared as internal briefs and selected public research. People multiplier (no direct reports) Mentor analysts and engineers; raise the security skill level across teams. Bar-raiser in security hiring loops. Key Milestones 30 days: Analyzed real threats end-to-end. Mapped the current response flow and where it breaks. Shipped at least one detection or mitigation to production. 90 days: Security response process and severity model published and agreed. Led at least one real campaign response with a written post-mortem. Baseline response metrics in place. 6 months: Time from first sighting to protection measurably reduced vs. baseline. First red-team review completed, top findings fixed. Working relationships with key external partners. 12 months: Recognized internally and externally as the owner of security response. Public research or disclosures published. Teams can run a standard campaign response without you. Requirements Must have 10+ years in security engineering, malware research, incident response, or offensive security, with several years leading cross-team work at Staff/Principal/Lead scope. Deep hands-on malware analysis and reverse engineering skills. Strong web application security and practical exploitation experience. Deep Linux knowledge from both the attacker's and the defender's side. Proven incident response leadership on large-scale events: you have run the response, written the advisory, and closed the post-mortem. Production coding in Python plus a systems language (Go, Rust or C). Experience with coordinated vulnerability disclosure and working with the security community. Clear, short writing for both engineers and non-technical stakeholders; works well async across time zones. Daily user of AI tools for analysis and coding, with critical judgment about their output. Nice to have Background in hosting or large web ecosystems. Detection authoring at scale (signatures, WAF/IDS rules). Kernel-level monitoring and rootkit detection. Threat intelligence practice and actor tracking. ML for malware classification. Public track record: CVEs, published research, talks, CTFs, open-source security tools. Relevant certifications are a plus, not a requirement. Benefits What's in it for you? Stay hands-on technically while owning complex, high-impact engineering work. Work on challenging Linux, automation, and cybersecurity problems across mature and newer products. Influence technical direction and make meaningful architectural decisions. Work independently with a high level of ownership and autonomy. Fully remote work with flexible working hours. 24 paid vacation days, 10 national holidays, and unlimited sick leave. Private medical insurance compensation. Co-working and gym/sports reimbursement. Education budget. Opportunity to receive a reward for innovative ideas that the company can patent. By applying for this position, you consent to the processing of your personal data as described in our Privacy Policy ( https://cloudlinux.com/candidate-privacy-notice ), which provides detailed information on how we maintain and handle your data.

Location: San Francisco, CA 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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. 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: $320,000 — $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. 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: Indianapolis, United States; Ohio City, United States; Chicago, United States About us: Shape the Future with AI, Ignite Your Potential Xenon7 is an inferno where skill, dedication and passion run together. About our client: Global healthcare leader headquartered in Indianapolis, Indiana. The Cardiometabolic Research (CMR) Therapeutic Area of our client, focuses on the discovery of biologic, small molecule and genetic therapeutics for the treatment of cardiometabolic diseases and associated complications. The Cloud and Connectivity organization is seeking an engineer in HPC platforms. This role will focus on enabling analytical, statistical, and scientific computing capabilities within high performance computing infrastructure. We are looking for an HPC Platform Engineer to help accelerate the next era of high performance computing innovation. What You’ll Be Doing You will be a leader the engineering and operations of design, build, and maintain scalable HPC platforms. You will play a crucial role in enabling HPC infrastructure and experiences. Collaborate with researchers and scientists to optimize performance and streamline workflows. Leverage tooling and automation for orchestration, resource scheduling, data access, and reproducibility. Evolve and operate public cloud and on-premises environments with a focus on availability and performance for HPC workloads. Define and monitor infrastructure metrics, resource utilization, among others. How You’ll Succeed Be Bold - You will bring a high learning agility and platform engineering skills to enable the Technology strategy, identifying opportunities to accelerate our HPC journey. Be Fast - You will advance initiatives to enable critical business projects. Be Proactive - You will have opportunities to leverage agile ways of working with a willingness to become an expert in deploying HPC solutions. Be Your Best - You will learn about new technologies in HPC. Requirements What You Should Bring Hands-on experience in HPC platforms, including knowledge of accelerators (e.g., GPU), HPC schedulers (e.g., Altair Grid Engine, Slurm), Kubernetes platforms, and containers technologies (Docker, Apptainer). Demonstrated experience in HPC workloads, infrastructure, and cluster architectures. Expertise with the Linux command line, Linux troubleshooting, and HPC administration. Experience with DevOps tools such as Github, Chef, Ansible, Terraform. Experience with automating infrastructure and applications. Passion for continual learning and staying informed of new technologies, infrastructure trends, and approaches in the HPC field. Strong programming and scripting skills in languages such as Python or Bash. Basic Requirements Bachelor’s degree in computer science, Information Technology, or related technical field. 5+ years’ experience HPC Platform Engineer. Demonstrated experience leading a global large-scale infrastructure project. Benefits Attractive, market-leading salary package. Clear career advancement path with professional development opportunities.

Location: Global; Ireland; Portugal; United Kingdom; Spain; Brazil; Colombia; South Africa; Canada Workplace: Remote ✨ ONE PLATFORM, A WHOLE WORLD OF OPPORTUNITY The best jobs have always clustered in a handful of the world's wealthiest cities. But talent is everywhere. Oyster set out to close that gap - building a global employment platform that lets companies hire, pay, and care for brilliant people anywhere. We're proof that a high-performing culture doesn't need an office. Distributed across 60+ countries since 2020, we've built something the industry keeps noticing: - Ranked #10 of 250 on TIME and Statista's 2026 list of America's Top WorkTech Companies https://www.oysterhr.com/library/oyster-hr-named-10-of-americas-top-worktech-companies-of-2026-by-time - Named one of America's Greatest Startup Workplaces 2026 https://www.oysterhr.com/library/oyster-2026-newsweek-award by Newsweek - A G2 Spring 2026 Leader https://www.oysterhr.com/library/oyster-named-best-roi-for-any-global-employment-platform-for-g2-spring-2026 across Employer of Record, Global Employment, Multi-country Payroll, and HR Compliance - The only B Corp-certified global employment platform ~ independently verified since 2023 Two of those rankings measured our business impact from the outside. One measured how our own people feel about working here. They landed in the same place ~ because at Oyster, culture and performance aren't separate conversations. They're the same one. And we're just getting started. If you want to do the best work of your career alongside people who care as much as you do, we'd love for you to apply. THE ROLE Location: While this position is posted in a specific location, all of Oyster’s positions are fully remote and you can work from home. Forever. To create the best experience for our new hire, this role requires you to be based within UTC−6 to UTC+3. Role Summary Oyster is hiring an Integrated Campaign Manager to lead the planning and execution of integrated growth campaigns for global prospective customers, turning target accounts into pipeline and accelerating open opportunities. Reporting to the Director of Demand Generation and Growth Marketing, you'll partner closely with our Product Marketing, Brand, Digital, Events, Ops, and Sales teams to deliver one coherent buyer journey across every channel. This is a role for a marketer who wants their work measured in pipeline, not page views. You’ll own Oyster’s integrated campaigns end to end. Deciding the strategy, the channel mix and the spend, and you’ll see directly how your work drives revenue. You’ll sit at the centre of Marketing and Sales, with the scope to shape how we reach companies hiring across borders. Key Responsibilities Demand Generation & Campaign Execution - Develop, execute and optimize multi-channel demand generation campaigns. Including content syndication, webinars, virtual events, email nurtures, direct mail, referral programs, and demo programs: to drive net-new pipeline and accelerate open opportunities. - Build quarterly campaign plans that balance always-on programs with high-impact moments for the full prospect lifecycle, modeled backward from pipeline goals to determine program mix and spend. - Partner with Product Marketing and Brand to turn positioning into campaign messaging, offers, and content that is tested and refined based on results. - Build campaign enablement (talk tracks, email templates, one-pagers) and align with BDRs on follow-up expectations so campaign interest converts into meetings. - Manage timelines, budget, and resources to ensure successful campaign delivery with ROI accountability. Cross-Functional Partnership & Continuous Improvement - Partner closely with stakeholders in marketing, sales, operations and external vendors to ensure consistent, aligned campaign execution across the business. - Optimize campaigns and refine strategies based on data-driven results, including A/B testing and performance reporting. - Identify opportunities to leverage AI and emerging technologies to improve research, segmentation, personalization, campaign development, content distribution, analysis, and execution. - Facilitate retrospectives and turn performance findings into optimized campaigns and repeatable playbooks. Core Requirements - 6+ years in B2B integrated or demand generation marketing, including substantial ownership of demand generation, integrated campaigns, growth marketing, or account-based marketing. - A track record of building campaigns that tie directly to pipeline coverage and revenue outcomes, not just engagement metrics. - Strong cross-functional collaboration skills. - Data-driven, with working knowledge of attribution and pipeline measurement. - Hands-on experience using AI tools for campaign planning, content acceleration, or workflow automation. - Experience with Salesforce and HubSpot, or equivalent CRM/MAP platforms. - Excellent written and verbal communication; comfortable presenting strategy and results to senior stakeholders. You'll also need - A reliable home internet connection and fluency in both written and spoken English. HOW WE WORK TOGETHER AT OYSTER Our values guide the work we do, the decisions we make, and the culture that makes Oyster what it is. We make it happen—progress is our default setting. We drive change, we build and give trust, and we move as one united team. Our mission is to create a more equal world of work: helping companies everywhere hire, pay, and care for talent anywhere. Everything we do ladders up to our mission. We embrace asynchronous, collaborative work and share how we operate in the Oyster Public HQ https://oysterhr.notion.site/Welcome-to-The-Reef-Oyster-s-Open-Source-Employee-Guide-fc482e3f107c4afd8c85ed217f1d0c1d so other global teams can learn from us. HOW YOU WORK With diverse locations, cultures, and needs, we created How YOU Work; https://oysterhr.notion.site/How-YOU-work-ac16c1932e314ffd8cb693e332458395 a program supporting your whole human experience at Oyster: - Work from anywhere: Oyster has no borders or HQ. As long as work is timely, your team is supported, and you're authorized to work where you live, you can work from anywhere. - Paid time off: Enjoy 40 days off per year (including holidays and vacation), or more if required by your country. - Mental health support: Access Plumm https://oysterhr.notion.site/Plumm-3b5e7e70dec6428e975f68f25972cfb7, our mental well-being service. - Wellbeing allowance: Each month, receive a wellbeing allowance in your ThanksBen wallet to spend on a wide range of options. - Flexible parental leave: All new parents are eligible for at least three months’ paid leave, with job protection for up to 12 months or as required locally. - WFH stipend: Receive a stipend for your laptop and home office equipment to get you set up quickly. ✨ THE BEST JOBS SHOULD BE AVAILABLE TO EVERYONE  We embrace diverse perspectives and intentionally build our product and company with an inclusive, global mindset. We encourage you to apply, even if you don’t meet every criterion, and are committed to a trust-based, thriving environment. Oyster is committed to ensuring equal opportunity of employment for qualified persons with disabilities and actively fosters an inclusive work environment. If you require reasonable accommodations throughout the recruiting process, please email jobs@oysterhr.com with the subject line: Interview Accommodations. Our available positions are on our careers page. Our team will only contact you from an @oysterhr.com email, and we will never ask for money as part of an interview process or job offer. If you receive a suspicious email about Oyster jobs or are directed to a site other than www.oysterhr.com/careers http://www.oysterhr.com/careers, please report it via our Compliance and Ethics Helpline https://faceup.com/c/8tpzyyye.

Location: Paris; Zurich; Warsaw; London ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE As a Research Software Engineer on the Sandboxes team, you will design, build, and operate the platform that runs isolated environments for untrusted code at massive scale. Our work spans distributed systems, low-level virtualization, and product-minded platform design. Engineers on this team move between deep infrastructure work and understanding how researchers actually use the platform. This is a software engineering role, not an ML research role. You do not need prior ML experience; what matters is writing clean, reliable systems code that scales. You will join a small, senior team where the wrong hire is worse than no hire. WHAT YOU WILL DO - Design, build, and operate the sandboxing platform that runs untrusted code at scale across multiple Kubernetes clusters, from our own bare metal data centers to hyperscalers. - Develop the sandbox runtime leveraging Firecracker, enabling fast startup, snapshotting, and efficient scheduling without blocking expensive hardware. - Obsess over performance and latency optimisation allowing us to reach millions of concurrent sandboxes. - Write robust, well-tested systems code in Rust and Python; review code, CI/CD, and observability across the platform. - Own cross-cluster networking, security boundaries, isolation guarantees and monitoring for suspicious activity. - Collaborate with researchers and ML engineers who use sandboxes for synthetic data generation and RL training, turning their needs into platform features. WHAT WE'RE LOOKING FOR - A strong background in software engineering and distributed systems, with experience building and operating large-scale infrastructure. - Deep expertise in at least one of: Kubernetes and cluster operations, cross-cluster networking, observability, or low-level virtualization. - Fluency in Python or Rust; comfortable writing systems code where performance and security matter. - Strong software-design instincts: modular code, testing, CI/CD, observability, and a bias for reliability. - A self-starter who learns fast. Core skills matter more than specific tools — we value meta-learning ability and motivation highly. - Low-ego, collaborative, and comfortable with ambiguity in a small, high-ownership team. NICE-TO-HAVES - Experience with Firecracker, microVMs, or similar virtualization technologies. - Product-mindedness: understanding of how sandboxes are used for synthetic data generation or RL training. - Experience with GPU clusters, CUDA, or ML workloads. - Prior SRE or platform engineering experience at scale. - Open-source contributions or widely used internal tools. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: United States, San Mateo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Manager, Software Engineering San Mateo, CA Role Overview Sony Interactive Entertainment LLC seeks a Manager, Software Engineering in San Mateo, CA to lead the delivery of common libraries targeting multiple projects across multiple platforms, owning the technical roadmap. Requirements Master’s degree in Computer Engineering, Electronic Engineering, or related field or equivalent, and two (2) years of experience working with Dev teams and improving services and infrastructural changes as a part of root cause analysis and resolution of incidents; creating and enhancing automation to ensure deployment of systems; enhancing infrastructures and auto-scale in the face of increasing network traffic or storage pressure; working with teams to implement requirements for Pub-Sub system (Kafka); setting up and maintaining monitoring for applications using Splunk and Yamas; setting up Splunk dashboards to read from local metric exporter and provide quick visibility into cluster state; leading projects to develop tools based on user’s requirements and usage, concentrated to reduce the troubleshooting time of engineers and improve visibility into the infrastructure; and in executing duties, utilizing tools including Chef, Screwdriver v2/v3, Jenkins, Pogo, Artifactory, and Git; and working with high-volume, highly-available messaging clusters including Kafka and Zookeeper, Hashicorp Consul, Kubernetes, Jenkins, Package management, Splunk, Monitoring systems, and Certificate and Identity management systems. Telecommuting and/or working from home may be permissible pursuant to company policies. Please refer to our Candidate Privacy Notice for more information about how we process your personal information, and your data protection rights. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $274,971.00 – $302,000.00/year Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: Remote (Worldwide) About Logos (λ) Logos (λ) is a movement of technologists, creatives, strategists, and activists working together to build a sovereign, people-owned technology stack that revitalises civil society and protects digital liberties at scale. This position is within the IFT Technical Services (IFT-TS) Distributed Systems Testing (DST) Team, a team that primarily supports Logos, while also contributing to other IFT projects. The role We are seeking an experienced Distributed Systems Evaluation Engineer to join the Institute of Free Technology - Technical Services, on the Distributed Systems Testing (IFT-TS DST) team. This role focuses on rigorously assessing the performance and reliability of IFT projects at scale, where Logos (λ) is one of them. Logos (λ) technology stack is composed of 3 main components: Logos (λ) Blockchain : Advanced privacy for a new era of decentralised applications and social institutions. Logos (λ) Messaging : Private peer‑to‑peer communication that resists surveillance and censorship. Logos (λ) Storage : Secure decentralised storage enabling fully decentralised apps and file sharing. We are looking for a talented and enthusiastic DevOps Engineer to join our Distributed Systems Testing (DST) team. You’ll be responsible for designing and executing comprehensive evaluation strategies, leveraging both large-scale lab deployments and protocol behavior modeling scripts. Your expertise will be crucial in analyzing these complex distributed systems, automating intricate test scenarios, and providing in-depth insights into system behaviors. Working closely with cross-functional teams, you’ll troubleshoot complex issues and translate technical data into actionable recommendations. Proficiency in containerization, cloud technologies, and distributed systems principles is essential. Key responsibilities Design, configure, and optimize Kubernetes clusters to support large-scale experiments and benchmarks of P2P technologies. Continuously improve cluster scalability and resource utilization, enabling increasingly complex deployments and experiments. Set up, maintain, and optimize supporting infrastructure such as monitoring, logging, and observability stacks (Grafana, Prometheus, Loki, etc.). Collaborate with DST researchers and engineers to streamline experimentation workflows and make analysis easier and more reproducible. Automate infrastructure and deployment workflows to increase reliability and reduce overhead. Troubleshoot, profile, and tune distributed workloads to ensure accurate and performant benchmarking. Identify, reproduce, and debug complex issues in distributed systems, working closely with Logos development teams. You ideally will have Strong experience with Kubernetes and container orchestration in production or research environments. Hands-on experience with libp2p/gossipsub Solid understanding of cloud infrastructure, Linux systems, and networking (especially relevant to distributed/P2P systems). Familiarity with monitoring and logging tools (Grafana, Prometheus, VictoriaLogs, etc.). Experience with infrastructure as code (Terraform, Ansible, Helm, etc.). Proficiency in at least one scripting/programming language (ideally Python). Interest in or experience with distributed systems, P2P networks, or blockchain technologies. Experience with networks and systems programming. Excellent written and conversational communication skills. Alignment with our core values and principles. Bonus points Hands-on experience with projects in the Logos collective. Background in performance benchmarking, scalability testing, or systems research. Contributions to open source projects. Experience working for an open-source organization. Interview Process Interview with our POps team Interview with team member from the IFT-TS DST team Pair programming & discussion of results Interview with IFT-TS team lead

- опыт коммерческой работы в DevOps или SRE от 4 лет; реальный опыт проектирования инфраструктуры с нуля, а не только поддержка существующей;

Задачи: — Участвовать в архитектурных решениях, проектировании, развитии и эксплуатации PaaS-платформы на базе Kubernetes, включая компоненты ClickHouse и Redis/Valkey. — Автоматизировать жизненный цикл Data Services: развертывание, масштабирование, миграции, обновления, резервное копирование, репликацию и восстановление. — Создавать и развивать решения самообслуживания для команд разработки. — Стандартизировать и развивать платформенные практики: Service Catalog, SLO/SLA, GitOps и IaC. — Участвовать в устранении инцидентов, анализировать стабильность и производительность платформы. — В первую очередь развивать платформенные компоненты для ClickHouse и Redis/Valkey, формировать стандартные сценарии их предоставления и эксплуатации в Kubernetes. Требования: — Понимание Kubernetes как платформы: архитектуры control plane и data plane, жизненного цикла объектов, примитивов нагрузки Deployments, StatefulSets и DaemonSets, механизмов контроля и reconciliation. — Уверенное знание Kubernetes storage stack: StorageClass, PVC/PV, особенности stateful-нагрузок, репликация и отказоустойчивость. — Практический опыт эксплуатации и тюнинга ClickHouse от 3х лет: репликация, шардирование, ClickHouse Keeper, оптимизация запросов и хранения, резервное копирование и восстановление. — Практический опыт эксплуатации Redis или Valkey: репликация, Sentinel или Cluster, механизмы персистентности, переключение при отказах, оптимизация памяти и задержек. — Опыт развертывания и эксплуатации stateful-операторов Kubernetes для ClickHouse и Redis/Valkey или участие в разработке и кастомизации собственных операторов. — Опыт работы с Terraform и понимание принципов IaC. — Опыт построения CI/CD pipelines для инфраструктурных компонентов. — Практическое владение GitOps-подходом, например Argo CD или Flux, и умение проектировать процессы развертывания платформенных компонентов. — Понимание процессов Software Development. Дополнительно приветствуется: — Опыт решения эксплуатационных задач, связанных с кластеризацией, высокой доступностью, backup/restore и производительностью других Data Services в Kubernetes. — Опыт разработки Kubernetes-операторов и контроллеров на Go или Python. — Опыт работы с multi-tenancy в Kubernetes. — Знание принципов распределенных систем: CAP, Raft, quorum и consensus. — Опыт участия в архитектурных обсуждениях и принятии решений при построении PaaS/DBaaS. — Опыт работы с policy-as-code: OPA, Gatekeeper или Kyverno. — Экспертиза в observability-стеке: Prometheus, Grafana, VictoriaMetrics и Jaeger, умение строить метрики и алерты для Kubernetes и Data Services. — Умение находить корневые причины инцидентов, связанных с latency, IO bottlenecks, сетью и потреблением памяти. — Опыт работы с Helm и проектирования production-чартов. Условия: — Полный рабочий день. — Возможна удалённая работа из любого города России. — Официальное трудоустройство, полностью белая зарплата. — Медицинское страхование (ДМС) и возможность онлайн-консультаций с врачами. — Возможность выступать на конференциях и писать статьи. — Собственный учебный центр с курсами, тренингами и книгами для повышения квалификации. — Офисы в Москве, Санкт-Петербурге и Новосибирске для гибридного формата работы.