Infrastructure Support Engineer in Amsterdam

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE You'll be the technical lead for one or two enterprise Account Executives covering [Health / Finance / MSPs / Public Sector] accounts in the Netherlands. You own the technical win: understanding what the customer is actually trying to do, designing the right data platform for it, proving it works, and getting it signed off. You'll spend most of your week with customers and partners, not in internal meetings. We've moved from all-flash arrays to the Enterprise Data Cloud — a single platform for block, file and object, on-prem and in the public cloud, with Portworx for Kubernetes workloads. In the Netherlands we sell through a strong partner channel and directly to some of the country's largest organisations, and the team is growing. WHAT YOU'LL DO.. Partner with your AE(s) on account strategy: which opportunities to pursue, how to position against the incumbent, what the customer's real decision criteria are Run discovery with infrastructure, platform and application teams; translate business requirements into architectures that hold up in production Design and present solutions across FlashArray, FlashBlade, Portworx, Evergreen and Pure Fusion — and know when something outside our portfolio is the right answer Own proofs of concept, benchmarks and competitive evaluations end to end Work alongside our Dutch partners (resellers, MSPs, system integrators) so the customer gets one coherent proposal, not two Lead techn

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, 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 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the modern ML stack (PyTorch and/or

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 production quickly and safely Own models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we're looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuitive grasp of overfitting, g

(FEQ327R229) The Solutions Architect (Lakebase) team executes on Databricks’ strategic Product Operating Model that provides enhanced focus on earlier stage, highly prioritised product lines in order to establish product market fit, and set the course for rapid revenue growth. They are part of a global go-to-market team mandate, though individually will cover a specific, local region. Clients may span across one or more business units and verticals. By working in partnership with direct account teams, they will jointly engage clients, foster the necessary relationships, position in-depth the specific product line, so as to provide compelling reasons for clients to adopt and grow the usage of the given product. They understand the appropriate approach, the guardrails, and the steps needed to successfully adopt the product line, as clients deliver on their business objectives. The Solutions Architect (Lakebase) is paired with an Account Executive aligned to a given product line with specific targets accordingly. Together, they will devise and implement a strategy across their assigned set of accounts, develop presentations, demos and other assets and deliver them such that clients make an informed decision as they decide to adopt the product-line in a meaningful way. The Lakebase product-line requires the following core technical competencies: 10+ years of transactional database (OLTP) expertise across engineering, product development, administration, and pre-sales, with a proven track record of designing and delivering client-facing solutions. Credibility in influencing OLTP products with the market insight needed to shape and prioritise roadmap capabilities. Experience architecting solutions that integrate transactional data systems within broader Big Data, Lakehouse, and AI ecosystems. Infrastructure, platform and administration expertise around disaster recovery, high availability, backup and recovery, scale-out methods, identity and security ma