Compute Country Lead in Amsterdam

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Staff Software Engineer focusing on AI Compute in the Together Cloud org, you will set technical direction for and build major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. This is an architect-and-build role. Fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes — you'll set the architecture for these across our global and in-DC s

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute in the Together Cloud org, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems: fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes. We solve them by building global and in-DC

About the Role We're looking for a Software Engineer to build the systems that treat infrastructure as software. This role owns the software state machines that provision hardware, bring it into service, and manage its full lifecycle — turning racks of GPUs into running inference clusters without a human touching a runbook. The Research and Inference team is your customer: today they file tickets and wait; the target state is that they issue a single API call to stand up, scale, or tear down a cluster, and the system takes care of the rest. The platform is manifest-driven such that teams declare the desired state of a cluster or host — shape, topology, software stack — and the system is responsible for reconciling reality to that manifest, continuously, through every stage of its lifecycle. You will design the engines that manifest the schema, the engines that execute against it, and the workflows that carry a piece of hardware or a cluster from one state to the next—taking it from bare metal to a fully functioning AI cluster for training or inference. You'll write production code which is typed, tested, versioned, and deployed through CI/CD that models infrastructure state and reconciles it, the same way a Kubernetes controller reconciles a cluster's desired state. Success looks like eliminating manual provisioning work, not documenting it better. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer expe

About the Role Together AI is looking for a Senior Network Engineer to design, deploy, and operate the global network infrastructure supporting our production services and high-performance AI compute environments. This is a hands-on engineering role for someone with deep networking expertise who can also troubleshoot across Linux, Kubernetes, automation, and application boundaries. You will work on large-scale, multi-vendor data center networks and help ensure they remain highly available, reliable, scalable, and performant. The ideal candidate has strong networking fundamentals, experience operating complex networks at scale, and a structured, evidence-based approach to troubleshooting. You should be comfortable owning problems from initial investigation through root cause and resolution, including situations where the issue may extend beyond the network itself. Requirements 8+ years of professional experience designing, building, and supporting large-scale production data center, cloud, service-provider, or high-performance computing networks (excluding enterprise networks). Deep understanding of TCP/IP and strong experience with technologies such as BGP, OSPF, VXLAN, EVPN, ECMP, and QoS. Experience designing and supporting multi-tenant network environments using technologies such as VRFs, VLANs, overlays, and policy-based segmentation. Hands-on experience deploying and troubleshooting network platforms from vendors such as Arista, Cisco, Juniper, and NVIDIA. Strong

About the Role Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure. As a Lead/Manager, you will play a key role in building the Together cloud platform engineering team in the Netherlands. We are a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal SaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world. Some of what you’ll work on: Work on a distributed GPU scheduling system for the on-demand clusters product, Instant Clusters. Build out a global management plane for managing our data center compute, networking, and storage. Design and build new customer-facing cloud platform services, delivering killer enterprise AI cloud features. Hybrid working 2 days a week at our offices in Amsterdam Responsibilities Lead/Manage a team of 8 together cloud Infrastructure Engineer in Amsterdam, Identify, design, and develop foundational backend services that power Together’s commerce platform Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure Partner wi

At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else. As a PhD Quantitative Research Intern, you'll spend 10-12 weeks pointing the research skills you've spent years building at markets. You'll collaborate with researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious. This isn't an internship where you observe from the sidelines, or re-run someone else's experiment. Outstanding work has the potential to shape production strategies and generate real, measurable returns. Ideal candidates are researchers who want to see their methods meet live markets: mathematicians, physicists, statisticians and computer scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London. What You'll Work On You'll work on real research problems, not simulated exercises. Your work would include: Discovering predictive patterns from billions of market events Designing statistical models that identify trading opportunities Applying probability, optimization and machine learning to open research problems Running large-scale simulations and experiments on high-performance research infrastructure Designing experiments and backtests to evaluate hypotheses Building AI-powered research agents that accelerate experimentation Developing infrastructure for rapid, lar

P-1324 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines and require speed and reliability. As a software engineer on the Storage and IO team at Databricks, you will be building the next generation of our cloud storage I/O platform supporting fast and reliable reads and writes against cloud storage systems. This specialized and highly optimized platform boosts the performance and reliability of the query processing system so it can outperform even specialized query engines. What we look for: BS (or higher) in Computer Science, related technical field or equivalent practical experience. Comfortable working towards a multi-year vision with incremental deliverables. Motivated by delivering customer value and impact.

About BlockTech BlockTech is a fast-paced algorithmic trading firm trading crypto derivatives and spot across global venues, 24/7, with our own capital. Crypto is one of the few markets where a researcher can still move the edge. The data is abundant, the microstructure is novel, and the loop between an idea and live PnL is short. High-frequency options trading is where we're strongest, and we're widening our scope to include more mid-frequency work. We're looking for a senior Quantitative Researcher with a mid-frequency background to join our Amsterdam trading floor. The role You'll be in charge of developing our mid-frequency capabilities, owning the research agenda end to end, from hypothesis and dataset construction through model training and backtesting to live deployment. You'll sit with traders, researchers, and analysts, and raise the bar for research across the floor. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 3+ years of quantitative

About BlockTech BlockTech is a fast-paced algorithmic market maker facilitating global derivatives and spot trading, originating from crypto markets and expanding into new markets. We trade our own capital on systems that run 24/7 and have to be fast and correct without exception. Our systems run on Linux and are written in Rust and Python. For the Summer of 2027, we're looking for Software Engineer Interns to join our engineering team in Amsterdam. The role This is an 8-10 week summer internship at our Amsterdam office, giving you a unique opportunity to work on an end-to-end project with a real and direct business impact. You’ll work in a small team and get the chance to understand how a trading firm actually works from the inside. You will Participate in a customized training program that will give you an understanding of financial markets in general, the company and the project. Own a project from design to deployment guided by experienced software engineers. Work with production-level data and systems Learn from the best, all while leveraging cutting-edge technology What we're looking for Currently in your (pen)ultimate year studying computer science or a related discipline at a top university in Europe Available full-time in Amsterdam, for a duration of 8 - 10 weeks over the summer of 2027, starting with 5th of July Proficiency in a systems language (ideally Rust and/orC++) and working knowledge of Python A solid grasp of data structures, algorithms, and what actually m

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research dir

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. You will: Collaborate closely with traders to translate research insights into systematic trading strategies Design, develop and deploy models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Build robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto is one of the few markets where the gap between a good model and live PnL comes down to how fast and how reliably you can ship it. Abundant data, novel microstructure, and a short path to production mean the quality of our infrastructure directly moves the edge. We're looking for a Quantitative Developer to build that infrastructure and get our models into production. The role This is a hands-on engineering seat on our trading floor. You'll own the infrastructure that turns research models into production trading systems, working primarily in Python and Rust, the language our models and systems are written in. You'll build the frameworks and tooling that let quants ship their code to production and keep those systems running once they're live. You'll work shoulder-to-shoulder with researchers, traders, and fellow engineers, building the tooling, pipelines, and standards that let good ideas reach production quickly and safely, and helping raise the engineering bar across the floor. You will Build and own the infrastructure that takes models from research to production - data pipelines, backtesting, deployment, and monitoring. Turn research prototypes into robust, performant, production-grade code that runs reliably in live trading Work closely with quantitative

About BlockTech BlockTech is a fast-paced algorithmic trading firm facilitating global cryptocurrency derivatives and spot trading while expanding into new markets. Positions, PnL, and hedging all run through our Mid-Office team. When the numbers our traders and risk team rely on are wrong, this is where it gets found and fixed. The role We're looking for a Software Engineer to join our Mid-Office team in this role, you'll own the systems that keep positions, PnL, and hedging correct across every venue we trade. You build and run the platform, and you're the one who notices when a number looks wrong and follows it until you know why. You will: Own the books. Maintain and evolve our position, trade, and PnL systems so they stay accurate across every venue. Do the quant work. Build and refine our hedging, Greeks, margin models, and early exercise premium calculations. Surface the risk. Build the risk views and calculations that show traders and the risk team what exposure we're carrying. Support the desk. Work side by side with traders and researchers, making sure the data they rely on is correct and available. Deliver reporting. Provide the data that internal stakeholders and regulators require, PnL breakdowns, trade surveillance, treasury accounting, and compliance. Own it in production. Spot discrepancies in live data, trace the root cause, and maintain what you ship. What we're looking for An engineer at heart with a strong quantitative background. Real enthusiasm for the e

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto is one of the few markets where the gap between a good model and live PnL comes down to how fast and how reliably you can ship it. Abundant data, novel microstructure, and a short path to production mean the quality of our infrastructure directly moves the edge. We're looking for a Quantitative Developer to build that infrastructure and get our models into production. The role This is a hands-on engineering seat on our trading floor. You'll own the infrastructure that turns research models into production trading systems, working primarily in Python and Rust, the language our models and systems are written in. You'll build the frameworks and tooling that let quants ship their code to production and keep those systems running once they're live. You'll work shoulder-to-shoulder with researchers, traders, and fellow engineers, building the tooling, pipelines, and standards that let good ideas reach production quickly and safely, and helping raise the engineering bar across the floor. You will Build and own the infrastructure that takes models from research to production - data pipelines, backtesting, deployment, and monitoring. Turn research prototypes into robust, performant, production-grade code that runs reliably in live trading Work closely with quantitative

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders,