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 are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work from France or any country in the Iberian Peninsula (Spain, Portugal, or Andorra).

Your responsibilities will include: 

• Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
• Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
• Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
• Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
• Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: 

• 5+ years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
• Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
• Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
• Excellent communication skills, fluency in French or Spanish preferred
• Customer-centric mindset

It will be an added bonus if you have: 

• Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
• Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
• Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) 

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.

Position Overview

We are seeking an Embedded Software Engineer to develop and maintain the company’s embedded software solutions, working with microcontrollers, RTOS environments, and data-driven tools to support testing, validation, and production systems.

Key Responsibilities:

• Develop and maintain software for the company’s devices.
• Program ARM microcontrollers in C/C++ within RTOS environments.
• Develop testing tools and test benches using Python.
• Process and analyze test data and results for evaluation and validation.
• Develop reporting systems, real-time visualizations, and dashboards.
• Integrate software with production management tools and systems.
• Implement and manage communication protocols including RF, Ethernet, USB, SPI, I2C, and UART.
• Participate in code reviews and ensure software quality.
• Manage technical documentation and version control using Git/GitLab, including submodules and collaborative workflows.
• Contribute to continuous improvement of team processes and methodologies.

Qualifications

Education:

Bachelor’s degree in Electronic Engineering, Computer Engineering, Telecommunications, or a related field.

Experience:

• Experience in embedded software development for microcontrollers and RTOS environments.
• Experience programming in C/C++.
• Experience developing tools and scripts in Python.
• Experience in data processing and analysis.
• Experience developing visualization, reporting, or dashboard tools.
• Experience with Git/GitLab and collaborative development workflows.

Preferred Qualifications:

• Knowledge of FPGA development and related technologies.
• Experience or interest in Artificial Intelligence and Machine Learning, particularly for data analysis, anomaly detection, and models based on PyTorch or TensorFlow.

Soft Skills:

• Proactive, autonomous, and results-oriented mindset.
• Strong analytical and problem-solving skills.
• Good communication skills and ability to work effectively in a team.
• Fluent level of English.

Technology Stack:

• C/C++
• Python
• ARM microcontrollers
• RTOS environments
• Git / GitLab
• Communication protocols: RF, Ethernet, USB, SPI, I2C, UART

Physical Requirements

Ability to work in a standard office environment and use a computer for extended periods.

This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands. 

We are now expanding our data capabilities and seeking an experienced Head / Director of Data Science to lead and scale our Data Science UA team function in Barcelona.

This role is ideal for a leader with a strong technical background, excellent people-management skills, and the ability to turn data into actionable, high-impact product and business outcomes.

Role Overview:

The Head / Director of Data Science will be responsible for building and growing our Data Science organization, driving advanced analytics and ML initiatives, and ensuring our products and business units are empowered by high-quality insights and predictive capabilities.

You will work closely with Product, Engineering, Revenue, and Leadership teams to translate business needs into DS/ML solutions, strengthen our data infrastructure, and support decision-making across the ecosystem.

This is a strategic and hands-on leadership role with significant influence on product evolution, optimization algorithms, and operational excellence.

Key Responsibilities:

Leadership & Strategy

• Lead and scale the Data Science function across the organization.
• Translate business and product goals into clear DS/ML initiatives and execution plans.
• Build and promote a strong data-driven culture across all teams.
• Applied Data Science & ML.
• Oversee development, deployment, and monitoring of ML models across Appodeal’s product and monetization ecosystem.
• Guide experimentation, modeling, uplift measurement, and algorithmic optimization.
• Ensure model quality, reliability, fairness, and performance at scale.
• Collaboration & Stakeholder Management.
• Partner with Product and Engineering teams to integrate Data Science into product roadmaps.
• Work with business units to identify opportunities, define DS/ML requirements, and deliver impactful insights.
• Communicate DS outcomes, metrics, and recommendations to leadership.

Team Leadership

• Lead, mentor, and develop a multidisciplinary team of Data Scientists, Analysts, and ML/AI specialists.
• Foster knowledge sharing, best practices, experimentation, and continuous improvement.
• Drive hiring, talent development, and team structure optimization.

Data Infrastructure & Governance

• Collaborate with Data Engineering and MLOps teams to ensure robust pipelines, feature stores, and model deployment workflows.
• Improve data quality, observability, and governance standards.

Qualifications:

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Math, or a related field (PhD is a plus).

Experience

• 5+ years of experience in Data Science, Machine Learning, or Applied Analytics.
• 3+ years in a DS leadership role (Lead DS, Head of DS, Director of DS, or similar).
• Demonstrated experience building and leading Data Science teams.
• Proven track record of delivering DS/ML solutions with real business impact.

Technical Skills

• Strong understanding of ML algorithms, experimentation, predictive modeling, and statistical analysis.
• Hands-on experience with Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and analytics tooling.
• Solid understanding of data pipelines, big data technologies, and collaboration with Data Engineering teams.
• Experience with AdTech, attribution, auction mechanics, or optimization algorithms is a strong plus.

Leadership & Soft Skills

• Excellent stakeholder management and communication skills.
• Ability to translate technical concepts into business language.
• Strong decision-making and prioritization abilities.
• Passion for mentoring, coaching, and building high-performing teams.

What We Offer:

• Opportunity to build and lead the Data Science function of a global product company.
• Direct influence on product roadmap and business outcomes.
• Collaborative and international team environment.
• Competitive compensation package and growth opportunities.
• A chance to shape the future of mobile app monetization.

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 Berlin office or full remote from any part of Germany.

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 (45min)
• 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

About Incode

Incode is a Series B unicorn rewriting how the world proves identity. Our AI-powered platform lets leading banks, fintechs, marketplaces, and governments deliver friction-free experiences while defeating fraud and safeguarding privacy. Customers such as Citi, AirBnB, Block, Chime, Sixt, and TikTok rely on Incode to power their identity verification and security.

Recently named a Leader in the Gartner® Magic Quadrant™ for Identity Verification, we’re scaling fast - and we’re looking for world-class Machine Learning Engineers to help us keep pushing the boundaries of biometric technology.

The Impact You’ll Make

As a Machine Learning Engineer at Incode, you’ll design, build, and deploy the deep learning models that power our most advanced technologies — from facial recognition and liveness detection to document processing and ID validation.

You’ll join a highly specialized engineering team working on solving complex, real-world challenges with cutting-edge ML architectures. Your work will directly influence how people verify their identity safely, seamlessly, and securely around the world.

What You’ll Own & Drive

• Innovate & Optimize - Develop and refine state-of-the-art deep learning models for computer vision applications such as facial recognition, liveness detection, and document processing and validation.

• Production-Ready Solutions - Architect and maintain scalable, efficient ML pipelines and ensure production-readiness and cost efficiency of deployed models.

• Research & Discovery - Stay at the forefront of academic and industry breakthroughs, experiment with emerging architectures and algorithms, and translate research into production-grade solutions.

• Data Mastery - Drive improvements in model performance through robust data preprocessing, cleaning, and analysis workflows.

• Collaborate & Communicate - Partner closely with research, product, and engineering teams to integrate ML solutions seamlessly into Incode’s production environment.

• Mentorship & Leadership - Provide technical guidance, share best practices, and contribute to building a culture of innovation and continuous learning.

Your Background

• 5+ years of industrial experience in Machine Learning, Deep Learning, or Computer Vision.

• Expertise in Python and deep learning frameworks such as PyTorch or TensorFlow.

• Demonstrated experience developing, deploying, and optimizing models for both performance and cost efficiency in production environments (including edge AI).

• Specialized expertise in at least one of the following areas:

  • Facial Recognition – face recognition, age estimation, facial attributes analysis.

  • Liveness Detection – facial authentication, anti-spoofing, and anti-deepfake defense.

  • Document Processing – OCR-based extraction, document analysis, and quality assurance.

  • ID Verification – biometric data authentication and document integrity validation.

• Proven ability to design and maintain end-to-end ML pipelines.

• Track record of research contributions or publications in deep learning and computer vision.

• Excellent communication and collaboration skills across cross-functional teams.

• Passion for mentoring talent and thriving in both long-term research and rapid iteration cycles.

The Qualities That Set You Apart

• Deep curiosity and technical excellence in AI and computer vision.

• Builder mindset with a drive to deliver real-world impact through applied research.

• Strong analytical thinking balanced by practical execution.

• Collaborative spirit and ability to simplify complex ideas for diverse audiences.

• Commitment to innovation, scalability, and continuous improvement.

Why Incode?