The role

We seek an experienced Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.

You’re welcome to work on-site in Amsterdam or remotely from any other EU country.

Your responsibilities will include:

• Designing customer-centric solutions that maximize business value and align with strategic goals.
• Building and maintaining long-term relationships to foster trust and ensure customer satisfaction.
• Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise.
• Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.

We expect you to have:

• 3+ years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or similar roles.
• Strong understanding of ML ecosystems, including models, use cases and tooling.
• Proven experience in setting up and optimizing distributed training pipelines across multi-node and multi-GPU environments.
• Hands-on knowledge of frameworks like PyTorch or JAX.
• Excellent verbal and written communication skills.

It will be an added bonus if you have:

• Expertise in deploying inference infrastructure for production workloads.
• Ability to transition ML pipelines from POC to scalable production systems.

Preferred tooling:

• Programming Languages – Python, Go, Java, C++
• Orchestration – Kubernetes (K8s), Slurm
• DevOps Tools – Git, Docker, Helm
• Infrastructure as Code (IaC) – Terraform
• ML Frameworks and Libraries – PyTorch, TensorFlow, JAX, HuggingFace, Scikit-learn

At IMC, technology is not a department; it’s at the heart of everything we do. Developed in-house, our innovative software makes millions of trading decisions daily, and we win by making better and faster decisions than our competition. Our various Python Development teams create scalable business-critical applications, tools and automated tasks to equip IMC’s Amsterdam, London, Zug and Mumbai trading and business support teams.

Your Core Responsibilities

IMC uses a wide variety of technologies. Python is widely used across our tech stack, notably to make it more accessible to our traders, researchers and analysts. As a Python Software Engineer at IMC Amsterdam, you will take part in the development of high-performance trading systems, analytical tools, signals generation, backtesting frameworks, trade management UIs or regulatory surveillance & risk monitoring. Therefore your role will involve collaborating directly and closely with the business and other tech teams, from initially gathering requirements to short iteration cycles to refine the implementation, to integrate user feedback, to voice and implement your improvements and ideas.

All the software you’ll be building is for internal use only, there are no external clients/users and therefore no non-sense requests: the users of your work sit a few meters from you and you have control over the whole development cycle. Curiosity and interest into the trading and financial markets is a key success factor in this role, as you will be working directly on the business logic, in an environment where understanding the business context is primordial.

At IMC we believe in giving a lot of responsibilities quickly, you’ll be working on your goals with a high degree of independence, yet supported by a solid network of mentors, teammates and trading team highly motivated to make sure you are successful and share their passion for trading and technology. In this role, you might end up working on are a wide range of tasks - for example:

• Adding a new signal a trader came up with to our framework.
• Supporting a trading desk in building the data analytics and visualisation tools they need.
• Troubleshooting, debugging or deep diving into performance analysis.
• Teaching others how to use our tech in their own scripts.
• Building and distributing internal python libraries.
• Starting whole new full-stack projects from scratch.

Your Skills and Experience

• We care about 4+ years of working experience as a Software Engineer.
• Deep technical knowledge of Python, you understand its internal workings and know its strength and limitation. We use a range of Python libraries and frameworks (such as FastAPI (AsyncIO), APScheduler, Pandas, Polars, RQ, Pytest, Tensorflow, scipy, xgboost, scikit-learn, numpy, numba, celery).
• Experience with DevOps, databases, big data or frontend frameworks is a plus. (Some examples of tools we frequently work with: Kubernetes, Helm, Docker, Gitlab CI, TypeScript, React, Redis, PostgreSQL, Mongo, Dremio, Apache Iceberg, HDFS, Kafka, Apache Arrow/Parquet).
• A critical mindset and the ability to challenge ideas and solutions, to not take things for granted, validate assumptions and dig into the details to find and cover all corner cases. You’re not afraid to ask questions and to speak up.
• Experience working with financial data is a must, ideally in the financial services industry. The nature of this role requires both affinity and experience to this type of data.

Our tech stack includes an ever-evolving range of systems and technologies, and our engineers have the freedom to choose the best solution for the problem at hand. If a new technology has the potential to add value, we’ll actively invest in exploring, adopting and developing it. 

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our Amsterdam office or full remote from any part of Netherlands.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
• Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
• Collaborate with research teams on innovative machine learning experiments
• Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring

• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
• Build tools to automate retraining, monitoring, and deployment of ML models
• Enhance collaboration features for ML stakeholders
• Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
  
  
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
• Optimize processing engines for scalability and latency
• Expand capabilities to support new databases and cloud platforms
• Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
  
  
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
• Develop customizable platforms for managing AI compliance and governance
• Simplify policy enforcement and integration across disparate systems
• Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45 min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote