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

The role

We’re looking for a Senior HPC Cluster Engineer to join our team and play a key role in the development of our cutting-edge hyperscaler platform. The GPU & InfiniBand team is responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus on GPU computing, InfiniBand networks, and the KVM/QEMU stack. You’ll work closely with hardware virtualization and device emulation technologies, ensuring high performance and security in multi-GPU, HPC environments. The role involves analyzing, troubleshooting, and improving infrastructure to support new hardware, fine-tuning system performance, and automating fault detection and resolution in a complex system.

In this position, you will be responsible for:

• Tuning the performance of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments.

• Analyzing and troubleshooting the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions.

• Integrating new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM.

• Enhancing automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments.

• Configuring and managing GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation.
  

We expect you to have:

• 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming).

• 3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning).

• In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems.

• Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python).

It would be a plus if you have:

• Experience with GPU end-to-end testing in a cluster environment using InfiniBand networking.

• Proven track record of analyzing and optimizing the performance of HPC workloads (e.g., simulations, data analysis, AI/ML workloads).

• Familiarity with RDMA, RoCE, and InfiniBand protocols for high-performance communication.

• Background in Software-Defined Networking (SDN) and experience with HPC cluster networking.

• Understanding of QEMU/KVM virtualization and managing virtualized environments.

• Experience with deep learning frameworks such as PyTorch and TensorFlow, and their integration with HPC systems.

• Familiarity with collective communication libraries like MPI and NCCL for distributed computing. 

We conduct coding interviews as part of the process.

The team

Customer experience at Nebius GPU AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are seeking a highly skilled and customer-focused leader to join our team as a Cloud Solutions Architect Lead. As a team leader, you will play a pivotal role in customer success across EU region, both managing the efforts of Cloud Solutions Architects team (technical and process excellence, talent development) and building processes alongside your stakeholders. Player-coach mentality and proven track record of managing high expertise teams is a must. 

You’re welcome to work from our office in Amsterdam or remotely from any EU country.

Your responsibilities will include: 

• Lead and mentor a team of Solutions Architects, fostering a culture of technical excellence, customer empathy, and collaborative execution.
• Oversee and participate in technical engagements including PoCs, workshops, architecture reviews, and trainings.
• Drive consistency and quality across infrastructure design, IaC practices, technical documentation, and customer enablement content.
• Collaborate closely with Product and Development teams, representing customer needs and helping shape the roadmap.
• Guide customers in optimizing ML/AI/HPC pipelines for performance, scalability, and cost-efficiency on Nebius  cloud infrastructure.
• Build visibility and ownership culture amongst Solutions Architects.

We expect you to have: 

• 5+ years of experience in a technical role (Solutions Architect, DevOps Engineer, ML Engineer, or similar) with a focus on cloud-native systems and distributed computing.
• 2+ years of experience leading or mentoring customer facing engineering teams.
• Deep hands-on experience with Infrastructure as Code (Terraform, Ansible), Kubernetes, and cloud automation.
• Strong communication and stakeholder management skills across both technical and non-technical audiences.
• Passion for developing scalable, reliable cloud architectures and driving customer success.

It will be an added bonus if you have: 

• Experience with HPC or ML orchestration frameworks (e.g., Slurm, Kubeflow, Ray).
• Strong coding skills in Python and experience with GPU computing environments for ML/AI workloads.
• Proficient in GPU stack components (e.g., CUDA, cuDNN) and cloud-native patterns for ML training/inference.
• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX).
• Understanding of cloud-based ML tools and offerings from NVIDIA, AWS, Azure, or Google Cloud.
• Experience participating in or leading technical contributions to conferences or open-source communities. 

The role

Nebius seeks a Key Customers Solutions Architect to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include: 

• Serve as the primary technical point of contact, troubleshooting and resolving complex AI/ML.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5 - 10 + years in roles like Cloud Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

The role

We are looking for a Customer Engineer to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Serve as the primary technical point of contact for troubleshooting and resolving complex AI/ML issues.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5+ years in roles like Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

This is Adyen

Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. 

For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.

Machine Learning Scientist

Adyen is looking for a Machine Learning Scientist to join our team in Amsterdam, a person sitting at the cornerstone of algorithms, mathematics, and engineering, who can solve problems by designing and implementing production-ready machine learning solutions. You will be responsible for building, developing and deploying algorithms that power data products at Adyen.

We are currently hiring for the following teams:

Insights - Diagnostics: The Insights team is at the core of this platform, providing the world’s largest merchants with the data and analytics they need to optimize their payment performance. Within this, our Proactive Diagnostics initiative acts as a proactive guard for merchant revenue, closing the loop between detecting an anomaly and providing a clear path to rectification. We operate at the intersection of Big Data and actionable intelligence. By leveraging Adyen’s global payment flow, we apply advanced statistical models and Causal Inference to not only detect performance drops but to explain the "why" behind them. We are looking for a Machine Learning Engineer to help us architect the next generation of our diagnostic engine.

Regulatory Reporting Technology: 

Adyen's Regulatory Reporting Tech team is seeking a Machine Learning Scientist to join us in Amsterdam. You will help in further automating and scaling our global regulatory reporting framework to keep Adyen compliant across all markets. Together with the team, you will implement key technical solutions to streamline our regulatory reporting operations. If you have a strong machine learning background and love solving complex problems, we want to hear from you.

In this role, you will: 

• Research, design, implement, train, deploy and monitor machine learning algorithms, either for batch prediction or real-time. Examples include: on-line learning algorithms to pick the best optimization decision in a changing environment, clustering algorithms to group customers/shoppers, supervised and semi-supervised learning methods for inference on risk patterns or graph analysis, representation learning for behavior prediction and monitoring, Anti-Money Laundering (AML) systems and real-time anomaly detection based on time-series modeling;
• Develop orchestrated pipelines for analytical purposes and machine learning training;
• Contribute to ongoing automation efforts for our experiments, training runs, validation runs and monitoring before, during and after deployment. Furthermore, collaborate with MLOps to improve our machine learning tooling;
• Collaborate closely with product managers and business stakeholders to understand requirements, define problems, and frame them as solvable machine learning tasks;
• Explore and analyze large, complex datasets to identify patterns, insights, and opportunities for ML-driven solutions;
• Define key performance metrics, design rigorous experiments (e.g., A/B tests), and perform statistical analysis to validate model performance and quantify business impact;

Who You Are:

• You have 5+ years of experience as a machine learning or data scientist;
• You have experience with the full machine learning model lifecycle in production flows;
• You have experience leveraging a big data framework to create the pipelines needed to feed the models with appropriate data;
• You have a good understanding of software engineering practices as well as data engineering and MLOps principles;
• You have knowledge of data science and statistics and machine learning techniques. These include a strong grounding in statistical inference, machine learning for prediction, and causal inference - Deep Learning experience is a plus;
• You have strong familiarity with the standard data science toolkit, such as (py)spark, (Trino) SQL, Tensorflow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow;
• You have an experimental mindset with a launch fast and iterate mentality. Extensive experience with designing and running experiments is essential;
• You are proactively taking the lead in projects, from ideation to deployment. You have experience working with a wide range of stakeholders and can clearly communicate complex outcomes over a wide range of audiences.
• You stay up-to-date with the latest research and developments in the machine learning field, and apply this where valuable.

Our Diversity, Equity and Inclusion commitments 

Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen. 

Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!

What’s next?

Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.

This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.

This is Adyen

At Adyen, we’re engineered for ambition. We empower our teams with the culture and support they need to own their careers. The people of Adyen are motivated problem-solvers who tackle unique technical challenges at scale, delivering innovative and ethical solutions to help the world’s best businesses achieve their ambitions faster, and we’re looking for a motivated Senior Machine Learning Engineer to join our team in Amsterdam.

Senior Machine Learning Engineer

The Customer Risk team is at the front line of this platform, building the next-generation systems required to assess and mitigate risk in real time. They are responsible for keeping our platform safe, while maintaining a seamless experience for our legitimate global merchants.

They operate at the critical intersection of high-stakes security and massive scale. By leveraging Adyen’s global payment flow, they are building a greenfield risk engine from scratch that moves beyond traditional detection to sophisticated, real-time entity assessment. We are looking for our first Senior Machine Learning Engineer to lead this effort and help architect the future of risk at Adyen.

In this role, you will:

• Lead – Act as the foundational ML Engineer for the Customer Risk team, taking the lead on the next-generation risk system from initial ideation and design to full production deployment.
• Build – Design and scale production-ready ML models for prediction, ranking, and embedding. You will own the end-to-end lifecycle, ensuring that our risk assessments are backed by robust, deep learning systems that can operate at Adyen’s massive scale.
• Architect – Develop the core ML infrastructure required to power our risk engine. You will build and manage the data processing pipelines, model evaluation frameworks, and deployment strategies that allow us to assess risk in real time with high reliability.
• Innovate – Bring our existing ML capabilities to the next level by introducing advanced software design and modular architecture to our modeling domains. You will bridge the gap between pure research and engineering excellence, ensuring our models are as maintainable as they are performant.
• Collaborate – Work closely with a high-performing product team and leadership to drive the risk roadmap. You will translate complex risk signals into clear business outcomes, directly impacting the safety and integrity of the Adyen platform.

Who You Are:

• You have an Engineering-First mindset. You treat Machine Learning systems as core production software, with 5+ years of experience ensuring that prediction, ranking, and deep learning models are as robust and reliable as any other part of the stack.
• You are a Software Craftsperson. You have 5+ years of experience navigating the full software development lifecycle, from initial testing to global launches. You are deeply proficient in Python, Java, or C/C++, focusing on writing clean, production-ready code that scales.
• You are an expert in the ML ecosystem. You have deep, hands-on experience with the standard Python data science toolkit—utilizing frameworks like TensorFlow, PyTorch, and XGBoost/LightGBM for modeling, and Spark, SQL (Trino), and Pandas for large-scale data manipulation.
• You are fluent in MLOps and Infrastructure. You don’t just build models; you operationalize them using MLFlow, Airflow, and Argo-workflows. You are comfortable working within modern infrastructure environments, leveraging Kubernetes and Docker for containerization, and ensuring system health through Prometheus and Grafana.
• You work end to end. You don’t just train models; you build the world they live in. You have 5+ years of hands-on experience designing end-to-end ML lifecycles, including data processing, model evaluation, deployment, and the fine-tuning required to keep systems performing at scale.
• You balance complexity with pragmatism. You possess 3+ years of dedicated software design and architecture experience. You understand how to build modular, maintainable systems in diverse modeling domains for the long-term.
• You are a Technical Leader. You take ownership of the roadmap, moving projects from ideation to production with confidence. You can translate high-level architectural needs into shipping solutions and have a proven track record of launching software products that deliver tangible impact.

Our Diversity, Equity and Inclusion commitments 

Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen. 

Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!

What’s next?

Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.

This role is based in Amsterdam. Our culture is built on the foundation of in-person collaboration, where our teams work side-by-side to solve unique challenges and accelerate growth. 

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

The Job in short

Over 75 million people interact with banking products built on Backbase. Every model you ship here touches real accounts, real decisions, and real financial lives - at scale. That's the standard this role is built around.

Backbase leads in AI-native banking technology, helping the world's biggest banks move from fragmented systems to unified frontlines where humans and AI agents work together. We power 100+ of the largest banks globally, and our AI capabilities sit at the core of that shift. 

As a Principal Machine Learning Engineer, you will define how intelligent systems operate in this environment: not just predicting outcomes, but making safe, auditable, and real-time decisions within a controlled execution model.

Reasons to build with us

Real-world impact at scale: Your models run in production for 150+ million end users across the globe's leading banks.

AI at the core: We're building the AI-native Banking OS from the ground up - ML engineering here shapes the product direction, not just the feature roadmap.

High-ownership culture: We ship early, iterate fast, and trust engineers to make decisive calls. You'll move at speed without layers of approval slowing you down.

"We don't debate AI in the abstract - we build it and put it in front of real banks. The engineers who thrive here are the ones who start with the problem, own the outcome, and raise the bar every sprint. That's the culture we've built, and it shows in what we ship.

- VP of Engineering, AI & Data

Meet the job

You'll be a key architect of Backbase's AI capabilities. That means moving fast, owning your work end-to-end, and building ML systems that solve real problems for banking partners - not theoretical models that gather dust.

That means:

● Designing, developing, and deploying production-grade ML models that personalize the banking experience and automate complex financial workflows

● Partnering with product and data teams to integrate AI capabilities directly into the Banking Platform

● Taking full ownership of the end-to-end ML lifecycle - from data discovery and feature engineering through to model monitoring and retraining

● Turning complex data architectures into clean, maintainable ML pipelines and APIs

● Running rigorous code reviews and mentoring mid-level engineers to keep raising the technical bar

● Identifying opportunities to apply AI where it removes friction and adds measurable value for end users

How about you

You're a seasoned engineer who thrives in a straight-talk culture. You don't settle for the industry standard - yesterday's best work is today's baseline, and you're always looking for what's next. Deep technical chops and a customer-first mindset aren't in tension for you; they're the same thing.

Your track record also shows:

● 5+ years designing and deploying large-scale ML systems in production environments

● Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, etc.)

● Experience with LLMs, RAG, or agent-based systems in production

Solid MLOps experience:

CI/CD for ML

model versioning

monitoring and observability

● Experience with data and streaming systems (e.g., Spark, Kafka)

● The ability to communicate complex technical concepts clearly to non-technical stakeholders, without oversimplifying or over-complicating

● A proven ability to make decisive technical choices, meet deadlines, and keep momentum in a fast-moving environment

Why Backbase

Backbase is where ambitious engineers come to do the most consequential work of their careers. We're growing fast, we build in the open, and we hold ourselves accountable to outcomes that show up in the real world - not just on slides.

We also offer:

● Competitive salary and performance-based bonus

● Flexible working arrangements and a hybrid setup

● Access to top-tier tools, cloud infrastructure, and ML platforms

● A learning budget to keep your skills sharp and your career moving

Collaborative teams across Amsterdam, Atlanta, Bangalore, and beyond

● A culture where straight talk is valued and good ideas win regardless of where they come from

● The chance to build AI systems that run at the scale of global banking - and see the results

At IMC, we believe technology is the foundation of our competitive edge — and machine learning is increasingly central to how we trade. Over the past few years, we've been steadily building our machine learning capabilities: developing infrastructure, growing our in-house GPU cluster, deploying models into production, and partnering closely with quant researchers and traders to generate real impact. Now we’re expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows.  We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform — influencing architecture, driving best practices, and solving high-leverage problems. You’ll work alongside researchers and technologists to design the systems that power experimentation, training, and deployment of ML models — and help set the direction for how machine learning is done at IMC as we scale. If you’ve built ML infrastructure at scale elsewhere and are looking for a role where your ideas will genuinely help shape our firm’s future — we’d love to hear from you.

Your Core Responsibilities: 

• Design and build end-to-end infrastructure for training, evaluation, and productionization of ML models, working closely with our HPC engineers who manage our on-prem compute cluster
• Influence foundational choices around data access, compute orchestration, experiment tracking, model versioning, and deployment pipelines
• Partner with quant researchers to accelerate iteration cycles, tighten feedback loops, and bring models from prototype to live trading
• Work with researchers to adapt and deploy modern architectures — transformers, state-space models, temporal convolutions, graph neural networks — to noisy, high-frequency financial data. Explore techniques like self-supervised pretraining, representation learning, and cross-sectional modelling where they offer genuine edge
• Shape our approach to reproducibility, continual learning, and production monitoring across a petabyte-scale data environment
• Define standards that create consistency across teams and geographies; mentor engineers and influence technical culture beyond your immediate work
• Keep pace with developments in deep learning research and ML infrastructure; bring ideas from academia and industry into how we work — whether that's new architectures, training techniques, or tooling

Your Skills and Experience: 

• 8+ years of experience building ML platforms or infrastructure at a leading tech company, research lab, or quantitative firm
• A track record of designing and owning large-scale training and inference systems — not just contributing, but architecting
• Deep proficiency in Python, with strong experience in either CUDA or C++
• Hands-on expertise with modern deep learning frameworks (PyTorch, TensorFlow, or JAX) and practical experience implementing architectures like transformers, attention mechanisms, or sequence models
• Strong foundation in deep learning fundamentals: optimization, regularization, loss design, and the trade-offs that matter when training at scale
• Experience with distributed training at scale (Horovod, NCCL) and GPU optimization (cuDNN, TensorRT)
• History of deploying models to production with strong observability, reproducibility, and monitoring practices
• Comfort working across the ML stack from data pipelines to training infrastructure to serving systems

Why This Role: 

• Build, don't inherit — You'll make foundational technology choices in a platform that's still being defined, not maintain someone else's legacy.
• Real investment, real backing — This is a strategic priority with resources behind it, not a side experiment.
• Direct impact on trading — Your infrastructure will power models that make real trading decisions in competitive global markets.
• Global scope — Work with teams across New York, Chicago, Amsterdam, London, Sydney, Hong Kong and beyond; define practices that can scale worldwide.
• Ideas over titles — IMC's culture values clarity, rigor, and collaboration. The best ideas win, regardless of where they come from.
• Tight coupling with research — You won't be building in isolation. Researchers and engineers work side-by-side, iterating together.

#LI-DNP

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement.

This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC’s technology and trading capabilities.

Your Core Responsibilities: 

• Develop large-scale distributed training pipelines to manage datasets and complex models
• Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems
• Develop libraries to improve the performance of machine learning frameworks
• Maximize performance in training and inference using GPU hardware and acceleration libraries
• Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions
• Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining
• Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs
• Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities
• Dig into the internals of open-source ML tools to extend their capabilities and improve performance

Your Skills and Experience: 

• 5+ years of experience in machine learning with a focus on training or inference systems
• Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus
• Strong engineering skills, including Python, CUDA, or C++
• Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX
• Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT)
• Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL)
• Exposure to cloud platforms and orchestration tools
• A track record of contributing to open-source projects in machine learning, data science, or distributed systems is a plus

#LI-DNP

WHO WE ARE 🌍

We help creators get more out of every conversation with Instagram-focused automations and support for other channels like Messenger, WhatsApp, and TikTok. The result? Better engagement, more sales, and real, sustainable growth.

With a diverse team of 350+ people spread across three continents, we’re building the leading Chat Marketing platform that is used — and loved — by more than 1.5 million customers worldwide.

WHO WE'RE LOOKING FOR 🌟

Manychat’s AI Core team turns ML and LLM ideas into production features used in millions of conversations every day. You will work across applied research, prototyping, and production delivery, partnering closely with our Python Platform team and Product to validate ideas quickly and ship high-impact AI workflows.

This role suits someone who loves to build fast, experiment, and take ownership of models, agents, and workflows end to end.

WHAT YOU’LL DO 🤖

• Design and deliver ML/LLM solutions end-to-end: fast prototyping, offline evaluation, and production rollout of models and agent workflows.
• Build and iterate on AI agents (RAG, vector search, memory, tools) using clear benchmarks and product metrics to guide improvements.
• Choose and implement the right approach for each problem (classical ML, LLMs, RAG pipelines, or agent architectures), defining data and labeling needs where required.
• Work closely with the Python Platform team to productionize your solutions with clean service boundaries, monitoring, and scalability in mind.

TO SHINE IN THIS ROLE 💥      

          Machine Learning & LLM Expertise

• Solid understanding of ML algorithms, metrics, search, RAG, and agent design. 
• Experience with frameworks like LlamaIndex, LangChain, or similar.
• Hands-on tuning with PyTorch, TensorFlow.
• Experience with LLM evaluation and benchmarking.
  
  Engineering Skills
• Strong Python engineering background, ideally three or more years in production environments.
• Experience building backend services (FastAPI, Docker, Pydantic, PostgreSQL).
• Familiarity with cloud environments and monitoring is a strong plus.
  
  Collaboration & Ownership
• Clear communication in English.
• Ability to work independently, iterate fast, and collaborate with product, data, and engineering teams.
• Product mindset and comfort working in a fast-moving environment.

WHAT WE OFFER 🤗

We care deeply about your growth, well-being, and comfort:

• 🌍 Hybrid onboarding to start work remotely and relocation support for you and your family.
• 💙 Comprehensive health insurance for both you and your family.
• 📚 Professional development budget for conference tickets, online courses, and other relevant resources to help you grow.
• 🫶 Flexible benefits package to tailor perks that matters most for you.
• 🪴 Hybrid work and generous leave options to prioritize your work-life balance.
• 🍽️ In-office perks, including free meals and snacks.
• 🤝 Company-funded sport activities, annual offsites and team-building events.

Manychat is an Equal Opportunity Employer. We’re committed to building a diverse and inclusive team. We do not discriminate against qualified employees or applicants because of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance.

This commitment is also reflected through our candidate experience. If you have individual needs that may require an accommodation during the interview process, please indicate this in your application. We will do our best to provide assistance throughout your interview process to ensure you’re set up for success.

With my application, I accept the Manychat Privacy Policy.

WHO WE ARE 🌍

We help creators get more out of every conversation with Instagram-focused automations and support for other channels like Messenger, WhatsApp, and TikTok. The result? Better engagement, more sales, and real, sustainable growth.

With a diverse team of 350+ people spread across three continents, we’re building the leading Chat Marketing platform that is used — and loved — by more than 1.5 million customers worldwide.

WHO WE'RE LOOKING FOR 🌟

Manychat’s AI Core team turns ML and LLM ideas into production features used in millions of conversations every day. You will work across applied research, prototyping, and production delivery, partnering closely with our Python Platform team and Product to validate ideas quickly and ship high-impact AI workflows.

This role suits someone who loves to build fast, experiment, and take ownership of models, agents, and workflows end to end.

WHAT YOU’LL DO 🤖

• Design and deliver ML/LLM solutions end-to-end: fast prototyping, offline evaluation, and production rollout of models and agent workflows.
• Build and iterate on AI agents (RAG, vector search, memory, tools) using clear benchmarks and product metrics to guide improvements.
• Choose and implement the right approach for each problem (classical ML, LLMs, RAG pipelines, or agent architectures), defining data and labeling needs where required.
• Work closely with the Python Platform team to productionize your solutions with clean service boundaries, monitoring, and scalability in mind.

TO SHINE IN THIS ROLE 💥     

          Machine Learning & LLM Expertise

• Solid understanding of ML algorithms, metrics, search, RAG, and agent design. 
• Experience with frameworks like LlamaIndex, LangChain, or similar.
• Hands-on tuning with PyTorch, TensorFlow.
• Experience with LLM evaluation and benchmarking.
  
  Engineering Skills
• Strong Python engineering background, ideally three or more years in production environments.
• Experience building backend services (FastAPI, Docker, Pydantic, PostgreSQL).
• Familiarity with cloud environments and monitoring is a strong plus.
  
  Collaboration & Ownership
• Clear communication in English.
• Ability to work independently, iterate fast, and collaborate with product, data, and engineering teams.
• Product mindset and comfort working in a fast-moving environment.

WHAT WE OFFER 🤗

We care deeply about your growth, well-being, and comfort:

• 🌍 Hybrid onboarding to start work remotely and relocation support for you and your family.
• 💙 Comprehensive health insurance for both you and your family.
• 📚 Professional development budget for conference tickets, online courses, and other relevant resources to help you grow.
• 🫶 Flexible benefits package to tailor perks that matters most for you.
• 🪴 Hybrid work and generous leave options to prioritize your work-life balance.
• 🍽️ In-office perks, including free meals and snacks.
• 🤝 Company-funded sport activities, annual offsites and team-building events.

Manychat is an Equal Opportunity Employer. We’re committed to building a diverse and inclusive team. We do not discriminate against qualified employees or applicants because of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance.

This commitment is also reflected through our candidate experience. If you have individual needs that may require an accommodation during the interview process, please indicate this in your application. We will do our best to provide assistance throughout your interview process to ensure you’re set up for success.

With my application, I accept the Manychat Privacy Policy.