senior machine learning engineer

Picnic Technologies

<div>
 In a nutshell
 
 
 As a Machine Learning Engineer at Picnic, you will design and deploy intelligent systems to solve our company&rsquo;s biggest challenges. Beyond building models, you will productionize them with strong monitoring and seamless integration into operational systems. You will collaborate closely with stakeholders to ensure the right problems are solved and that solutions deliver real-world impact.
 
 
 All using high quality data. Our data is registered, logged, and consistent, enabling you to focus on building and improving models rather than cleaning data. This role combines the skills of a consultant, software engineer, and applied mathematician.
 
 
 Tricks of the trade
 
 
 You will definitely:
 
 
 <ul>
 <li>
 Identify and execute improvement possibilities together with other ML Engineers and (product) analysts
 </li>
 <li>
 Collaborate on your project from inception to production, to continuous improvement
 </li>
 <li>
 Develop tools and enhancements for our cloud-based Machine Learning platform
 
 
 
 </li>
 </ul>
 You could work on various projects and fields, such as:
 
 
 <ul>
 <li>
 Demand forecasting: delivery, article, trip volumes, used Picnic-wide
 </li>
 <li>
 Fraud detection: helping us keep troublemakers out of our store
 </li>
 <li>
 Recommendation systems: generating useful in-app grocery suggestions
 </li>
 <li>
 Search and ranking: helping our customers find exactly what they need
 </li>
 <li>
 Predicting delivery drop-off times: making sure we&rsquo;re on-time at every customer&rsquo;s door
 </li>
 <li>
 Vision: ensuring quality control and smooth operations within our warehouses
 
 
 
 </li>
 </ul>
 Check out some of our previous machine learning projects here: https://blog.picnic.nl/tagged/machine-learning
 
 
 We&rsquo;re looking for
 
 
 <ul>
 <li>
 Master&rsquo;s degree or higher in AI, Computer Science, Mathematics, or a related field
 </li>
 <li>
 5+ years of experience in data science or applied machine learning
 </li>
 <li>
 Excellent communication skills, you can clearly explain complex ideas in non-technical terms and enjoy working closely with business stakeholders to solve problems together
 </li>
 <li>
 Experienced in designing, deploying, and maintaining production ML systems, with solid software engineering and ML principles
 </li>
 <li>
 Strong Python and SQL skills
 </li>
 <li>
 Able to define the long-term vision and technical architecture for ML solutions within your domain
 </li>
 <li>
 Experience with Docker, Kubernetes, and CI is a plus
 
 
 
 </li>
 </ul>
 Picnic Perks
 
 
 
 🫱🏼&zwj;🫲🏾 Teamwork makes the dream work
 
 
 
 With more than 80 nationalities across 3 countries, you&rsquo;ll be part of a diverse company with plenty of cool stuff to get involved with, from board game evenings to after-work drinks to our company ski trip and more!
 
 
 
 💡 Make a difference
 
 
 
 You&rsquo;ll work in an awesome startup environment with the freedom to drive your own projects and create a visible impact. Our fully electric vehicles and sustainable business model mean you&rsquo;ll also be contributing to making the world a better place!
 
 
 
 🥗 Fresh Lunch, coffee, and snacks
 
 
 
 Our offices are equipped with fully-fledged coffee bars and a kitchen and chefs. They prepare delicious fresh and warm lunches every day so you can keep your energy up.
 
 
 
 🚲 Health insurance discount &amp; bike plan
 
 
 
 We have a partnership with CZ (a health insurance provider). Picnic employees get a discount on CZ insurance packages between 5% and 15%. Furthermore, through our partnership with Lease a Bike, you can rent-to-own a new (e)bike at a discounted rate
 
 
 
 🌎 Relocation
 
 
 
 If you&rsquo;re moving from another country to join Picnic we make it as smooth as possible for you. We&rsquo;ll cover your flight costs for you and your partner and kids, your first month's rent and moving costs (up to &euro;2000), and help you with the 30% tax ruling setup and application.
 
 
 
 📆 All the rest
 
 
 
 At Picnic you get 25 holidays, we cover your travel expenses and offer a pension plan. And your phone and laptop are on us, as well.
</div>

Senior Machine Learning Engineer

IMC Trading

<div>
 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&rsquo;s technology and trading capabilities.
 
 
 
 Your Core Responsibilities
 
 
 
 <ul>
 <li>
 The opportunity to be in a brand new position in a growing team
 </li>
 <li>
 Develop large-scale distributed training pipelines to manage datasets and complex models
 </li>
 <li>
 Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems
 </li>
 <li>
 Develop libraries to improve the performance of machine learning frameworks
 </li>
 <li>
 Maximize performance in training and inference using GPU hardware and acceleration libraries
 </li>
 <li>
 Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions
 </li>
 <li>
 Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining
 </li>
 <li>
 Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs
 </li>
 <li>
 Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities
 </li>
 <li>
 Dig into the internals of open-source ML tools to extend their capabilities and improve performance
 
 
 </li>
 </ul>
 
 Your Skills And Experience
 
 
 
 <ul>
 <li>
 5+ years of experience in machine learning with a focus on training or inference systems
 </li>
 <li>
 Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus
 </li>
 <li>
 Strong engineering skills, including Python, CUDA, or C++
 </li>
 <li>
 Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX
 </li>
 <li>
 Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT)
 </li>
 <li>
 Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL)
 </li>
 <li>
 Exposure to cloud platforms and orchestration tools
 </li>
 <li>
 A track record of contributing to open-source projects in machine learning, data science, or distributed systems is a plus
 
 
 </li>
 </ul>
 
 About Us
 
 
 
 IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we&rsquo;ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.
</div>

Machine Learning Engineer

Cloudbeds

<div>
 
 
 
 
 What Makes Us Unique&nbsp;
 
 
 
 
 
 
 At Cloudbeds, we're not just building software, we&rsquo;re transforming hospitality. Our intelligently designed platform powers properties across 150 countries, processing billions in bookings annually. From independent properties to hotel groups, we help hoteliers transform operations and uplevel their commercial strategy through a unified platform that integrates with hundreds of partners. And we do it with a completely remote team. Imagine working alongside global innovators to build AI-powered solutions that solve hoteliers' biggest challenges. Since our founding in 2012, we've become the World's Best Hotel PMS Solutions Provider and landed on Deloitte's Technology Fast 500 again in 2024 &ndash; but we're just getting started.&nbsp;
 
 
 
 Location - Remote (Europe)
 
 
 
 
 
 
 How You'll Make an Impact:
 
 
 
 
 
 As a
 
 Staff Machine Learning Engineer
 
 
 
 , you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.
 
 
 You&rsquo;ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You&rsquo;ll be instrumental in establishing robust ML practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you&rsquo;ll own the end-to-end development of our revenue management application&mdash;ensuring hotels have the reliable, accurate insights they need to maximize their success.
 
 
 
 Our Machine Learning Team:
 
 
 
 
 
 Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms.&nbsp;
 
 
 We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency.&nbsp;
 
 
 People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.
 
 
 
 What You Bring to the Team:
 
 
 
 
 <ul>
 <li>
 Architectural Expertise: Proven track record in designing, deploying, and maintaining production-grade, distributed ML systems (Sagemaker)
 </li>
 <li>
 Deep MLOps Proficiency: Expert-level knowledge of CI/CD, orchestration (e.g., Apache Airflow, Flink), and model monitoring/drift detection at scale.
 </li>
 <li>
 Software Engineering Rigor: Strong background in Python, distributed systems, and backend development, with a firm grasp of software engineering best practices.
 </li>
 <li>
 Technical Strategy: Experience defining SLIs/SLOs and managing large-scale technical roadmaps.
 </li>
 <li>
 Leadership: Demonstrated ability to influence cross-functional teams, mentor junior talent, and drive consensus on complex technical decisions.
 </li>
 <li>
 Domain Knowledge: Ability to apply statistical and ML methods to optimize revenue management and pricing strategies.
 </li>
 </ul>
 
 
 What Sets You Up for Success:
 
 
 
 
 <ul>
 <li>
 5+ years of experience in a machine learning role, with demonstrated success in ML Engineering and deploying models to production.
 </li>
 <li>
 Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
 </li>
 <li>
 Great understanding of machine learning principles (experimental design, statistical distributions and test, machine learning algorithms)
 </li>
 <li>
 Expertise in deploying ML models at scale on AWS, with experience using MLFlow, Sagemaker or similar platforms.
 </li>
 <li>
 Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews, using Docker, Terform, Kubernetes).
 </li>
 <li>
 Expert-level SQL skills and experience working with large datasets for analysis and modeling.
 </li>
 <li>
 Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
 </li>
 <li>
 Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.
 </li>
 <li>
 Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
 </li>
 </ul>
 
 
 Bonus Skills to Stand Out (Optional):
 
 
 
 
 <ul>
 <li>
 Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
 </li>
 <li>
 Experience with data quality monitoring tools and frameworks.
 </li>
 <li>
 Master&rsquo;s or PhD in Computer Science, Mathematics, or a related field.&nbsp;
 </li>
 </ul>
 
 
 
 
 
 What to Expect - Your Journey with Us&nbsp;
 
 
 
 
 
 Behind Cloudbeds' revolutionary technology is a team of redefining what's possible in hospitality. We're 650+ employees across 40+ countries, bringing together elite engineers, AI architects, world-class designers, and hospitality veterans to solve challenges others haven't dared to tackle. Our diverse team speaks 30+ languages, but we all share one language: a passion for innovation and travel. From pioneering breakthroughs in machine learning to revolutionizing how hotels operate, we're not just watching the future of hospitality unfold &ndash; we're coding it, designing it, writing it and shipping it. If you're ready to work alongside some of the brightest minds in tech who are obsessed with using AI to transform a trillion-dollar industry, this is your chance to be part of something extraordinary.
 
 
 Learn more online at
 
 cloudbeds.com
 
 
 
 
 
 Company Awards to Check Out!&nbsp;
 
 
 
 
 <ul>
 <li>
 Best All-In-One Hotel Management System | HotelTechAwards (2025)
 </li>
 <li>
 Overall 10 Best Places to Work | HotelTechAwards (2025)
 </li>
 <li>
 Most Loved Workplace&reg; Certified (2024)&nbsp;
 </li>
 <li>
 Top 10 People&rsquo;s Choice(2024)
 </li>
 <li>
 Deloitte Technology Fast 500 (2024)
 </li>
 </ul>
 &nbsp;
 
 
 
 Discover our Benefits:
 
 
 
 
 <ul>
 <li>
 Remote First, Remote Always&nbsp;
 </li>
 <li>
 PTO in accordance with local labor requirements
 </li>
 <li>
 Monthly Wellness Fridays - enjoy an extra long weekend every month
 </li>
 <li>
 Full Paid Parental Leave
 </li>
 <li>
 Home office stipend based on country of residency
 </li>
 <li>
 Professional development courses in Cloudbeds University
 </li>
 <li>
 Access to professional development, including manager training, upskilling and knowledge transfer.
 </li>
 </ul>
 
 
 
 Everyone is Welcome - A Culture of Inclusion&nbsp;&nbsp;
 
 
 
 
 
 
 Cloudbeds is proud to be an Equal Opportunity Employer that celebrates the diversity in our global team! We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
 
 
 
 
 Cloudbeds is committed to the full inclusion of all qualified individuals. As part of this commitment, Cloudbeds will ensure that persons with disabilities are provided reasonable accommodations in the hiring process. We encourage deaf, hard of hearing, deaf-blind, and deaf-disabled individuals to apply. If reasonable accommodation is needed to participate in the job application or interview process or to perform essential job functions, please contact our HR team by phone at (858) 201-7832 or via email at
 
 accommodations@cloudbeds.com
 
 . Cloudbeds will provide an American Sign Language (ASL) interpreter where needed as a reasonable accommodation for the hiring processes.
 
 
 
 
 To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Cloudbeds. Staffing, recruiting agencies, and individuals being represented by an agency are not authorized to use this site or to submit applications, and any such submissions will be considered unsolicited. Cloudbeds does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Cloudbeds employees, or any other company location. Cloudbeds is not responsible for any fees related to unsolicited resumes/applications.
 
 
 
 
</div>

Staff ML Engineer

Xccelerated | Part of Xebia

<div>
 
 Data Engineer
 
 
 
 
 
 
 Location:
 
 Netherlands (hybrid)
 
 
 
 Language:
 
 English-speaking environment
 
 
 
 
 
 Are you a
 
 Data Engineer based in Europe
 
 who wants to take the next step in your career?
 
 
 Would you like to
 
 relocate to the Netherlands
 
 and work on a modern cloud-based data platform while accelerating your growth through structured, high-level training?
 
 
 
 
 
 At
 
 Xccelerated
 
 , we are looking for
 
 Medior Data Engineers
 
 to help build a
 
 state-of-the-art data platform on Google Cloud Platform (GCP)
 
 . You&rsquo;ll work alongside experienced consultants and follow an intensive training program designed to rapidly strengthen your technical and professional skills.
 
 
 
 
 
 💡 Why join Xccelerated?
 
 <ul>
 <li>
 Build a
 
 modern data platform from scratch
 
 on Google Cloud Platform
 </li>
 <li>
 Work on real client projects while continuously improving your skills
 </li>
 <li>
 Receive
 
 60+ days of structured technical training
 
 led by experienced Tech Leads
 </li>
 <li>
 Collaborate with international engineering and analytics teams
 </li>
 <li>
 After one year, transition to a
 
 direct contract with the client organization
 
 </li>
 </ul>
 
 
 
 
 🚀 Your role as a Data Engineer
 
 
 As a Data Engineer at Xccelerated, you will help lay the foundation for data-driven decision making.
 
 
 You will:
 
 <ul>
 <li>
 Design, build and maintain
 
 scalable data pipelines
 
 on GCP
 </li>
 <li>
 Develop components of a modern data platform supporting analytics and machine learning use cases
 </li>
 <li>
 Ensure reliable integration between data sources, pipelines and data models
 </li>
 <li>
 Work closely with engineering, analytics and cloud teams on architecture and implementation
 </li>
 <li>
 Continuously improve data quality, reliability and performance
 </li>
 </ul>
 
 
 
 
 👩 💻 Who we&rsquo;re looking for
 
 
 You&rsquo;re a hands-on engineer who enjoys learning by doing and working on meaningful data challenges.
 
 
 You bring:
 
 <ul>
 <li>
 A Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data, Cloud or a related field
 </li>
 <li>
 
 3&ndash;4 years of experience
 
 as a Data Engineer (or similar role)
 </li>
 <li>
 Strong skills in
 
 Python
 
 and
 
 SQL
 
 </li>
 <li>
 Experience with at least one public cloud:
 
 GCP, AWS or Azure
 
 </li>
 <li>
 Familiarity with modern data tools such as
 
 Spark, Databricks or Airflow
 
 </li>
 <li>
 A proactive mindset and willingness to
 
 relocate to the Netherlands
 
 </li>
 </ul>
 
 
 
 
 🎁 What we offer
 
 
 At Xccelerated, we offer more than just a job &mdash; we offer a
 
 career accelerator in Data &amp; Cloud
 
 .
 
 <ul>
 <li>
 Competitive salary based on experience
 </li>
 <li>
 
 Relocation support
 
 for candidates moving to the Netherlands
 </li>
 <li>
 25 vacation days
 </li>
 <li>
 Intensive onboarding with a hands-on technical bootcamp
 </li>
 <li>
 Weekly technical training, mentoring and innovation days
 </li>
 <li>
 Company laptop and modern tooling
 </li>
 <li>
 Great lunches, excellent coffee and a well-stocked snack bar
 </li>
 <li>
 Hybrid working model and an international team
 </li>
 </ul>
 
 
 
 
 🌍 About Xccelerated
 
 
 Xccelerated (part of the
 
 Xebia Group
 
 ) is a tech accelerator focused on developing the next generation of Data &amp; Cloud professionals.
 
 
 You&rsquo;ll work
 
 four days per week
 
 on real client projects and spend
 
 one day per week
 
 on structured training, coaching and innovation. After one year, you&rsquo;ll have the opportunity to join one of our partner companies directly.
 
 
 
 
 
 📩 Interested in relocating to the Netherlands?
 
 
 We&rsquo;d love to hear from you.
 
 
 📧 Contact:
 
 Samantha Goncalves
 
 &ndash; sgoncalves@xccelerated.io
 
 
 📞 Phone: +31 6 13889770
 
 
 
 
 
 📋 Application process
 
 <ol>
 <li>
 Introductory interview with one of our recruiters
 </li>
 <li>
 Technical assessment &amp; presentation with one of our Tech Leads (remote)
 </li>
 </ol>
 
 We aim to complete the process within
 
 1&ndash;3 weeks
 
 , depending on availability.
 
</div>

Data Engineer (Relocation to the Netherlands)

Optics11

<div>
 We are expanding our team with a
 
 Data &amp; ML Infrastructure Engineer
 
 who will take ownership of the platform that enables data ingestion, processing, storage, and machine learning workflows across multiple products. Operating at the intersection of data science, software engineering, and cloud infrastructure, you will build the foundations and ensure that our ML systems are scalable, reproducible, and production ready.
 
 
 In this role, you will design, implement, and continuously improve a cloud-agnostic data and ML platform that supports multiple products and teams. You will be responsible for platform reliability, scalability, and cost-efficiency, while providing data scientists and ML engineers with the tools and infrastructure to efficiently develop, train, validate, and deploy machine learning models. You will serve as a technical bridge between the data science and IT/infrastructure teams, translating requirements into robust and maintainable systems.
 
 
 This role includes ownership of an existing vendor-delivered platform and its evolution into a fully automated, reproducible, and multi-product ML platform.
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Design, implement, and maintain the data and ML platform infrastructure, including systems for data ingestion, storage, processing, and training.
 </li>
 <li>
 Ensure high availability, reliability, and uptime of the platform, as it is critical to the business value proposition.
 </li>
 <li>
 Maintain and evolve vendor-delivered platform components and ensure long-term maintainability and independence.
 </li>
 <li>
 Build and maintain data workflows, including tools for dataset versioning, experiment tracking, and model lifecycle management across multiple products.
 </li>
 <li>
 Enforce DevOps / MLOps practices, including CI/CD pipelines, Infrastructure-as-Code, and automated workflows.
 </li>
 <li>
 Develop cloud-agnostic and containerized solutions that can run across public and private cloud environments within EU constraints.
 </li>
 <li>
 Optimize data storage, lifecycle policies, and cost efficiency, including tiered storage and retention strategies.
 </li>
 <li>
 Implement and maintain monitoring and alerting systems (e.g., Prometheus, Grafana) for pipelines, infrastructure, and resource usage.
 </li>
 <li>
 Ensure data governance, security, and compliance, including access control, audit logging, and anonymization requirements.
 </li>
 <li>
 Collaborate closely with data scientists, ML engineers, and IT teams to deliver infrastructure that meets operational needs.
 </li>
 <li>
 Manage resource and cost controls, including budgets, approvals, and tracking.
 </li>
 <li>
 Contribute to documentation, operational runbooks, and onboarding materials for the platform.
 
 
 
 </li>
 </ul>
 
 Why Join Us?
 
 
 
 <ul>
 <li>
 Join one of Europe&rsquo;s most promising deep-tech scale-ups.
 </li>
 <li>
 Shape the future of a rapidly growing multidisciplinary R&amp;D organization.
 </li>
 <li>
 Competitive salary and benefits package.
 </li>
 <li>
 Enjoy regular team activities and company events.
 </li>
 <li>
 Fresh team lunches provided3 times/ week.
 
 
 
 </li>
 </ul>
 Required Qualifications:
 
 
 <ul>
 <li>
 MSc or equivalent with 5+ years&rsquo; industry experience in Computer Science, Data Engineering, Machine Learning, or a related field.
 </li>
 <li>
 Strong experience with data platforms, cloud infrastructure, and distributed systems (AWS, GCP, Azure).
 </li>
 <li>
 Proven experience with Infrastructure-as-Code (e.g., Terraform) and automated deployments.
 </li>
 <li>
 Experience with ML platforms and tools (MLflow, Feast, DVC, DataHub or equivalent).
 </li>
 <li>
 Experience with AWS Sagemaker or Google Vertex AI platforms.
 </li>
 <li>
 Experience with databases (MongoDB, PostgreSQL, InfluxDB or equivalent).
 </li>
 <li>
 Experience with message brokers and streaming systems (Kafka, RabbitMQ or equivalent).
 </li>
 <li>
 Hands-on experience with containerization (Docker/OCI) and orchestration (Kubernetes or similar).
 </li>
 <li>
 Experience with CI/CD systems (e.g., GitLab CI).
 </li>
 <li>
 Programming skills in Python.
 </li>
 <li>
 Experience with monitoring and observability tools (Prometheus, Grafana).
 </li>
 <li>
 Understanding of DevOps and MLOps practices.
 </li>
 <li>
 Ability to work across teams and translate requirements into scalable infrastructure solutions.
 
 
 
 </li>
 </ul>
 
 Nice to Have:
 
 
 
 <ul>
 <li>
 Knowledge of data governance, IAM, and security frameworks.
 </li>
 <li>
 Experience with cost optimization and resource management in cloud environments.
 </li>
 <li>
 Familiarity with multi-tenant or multi-product platform architectures.
 </li>
 <li>
 Experience working with EU data compliance constraints in energy, maritime or defense.
 
 
 
 </li>
 </ul>
 
 Security &amp; Compliance:
 
 
 
 You'll be working with clients in the defense and security sectors, obtaining a Certificate of No Objection issued by the AIVD (Dutch General Intelligence and Security Service) is mandatory. This means you will need to undergo a security screening. For more information, please refer to details on security screening.
</div>

Data & ML Infrastructure Engineer

<div>We are expanding our team with a Data &amp; ML Infrastructure Engineer who will take ownership of the platform that enables data ingestion, processing, storage, and machine learning workflows across multiple products. Operating at the intersection of data science, software engineering, and cloud infrastructure, you will build the foundations and ensure that our ML systems are scalable, reproducible, and production ready.
In this role, you will design, implement, and continuously improve a cloud-agnostic data and ML platform that supports multiple products and teams. You will be responsible for platform reliability, scalability, and cost-efficiency, while providing data scientists and ML engineers with the tools and infrastructure to efficiently develop, train, validate, and deploy machine learning models. You will serve as a technical bridge between the data science and IT/infrastructure teams, translating requirements into robust and maintainable systems.
This role includes ownership of an existing vendor-delivered platform and its evolution into a fully automated, reproducible, and multi-product ML platform.<h4 class="jobSectionHeader">
Key Responsibilities:</h4><ul><li>
Design, implement, and maintain the data and ML platform infrastructure, including systems for data ingestion, storage, processing, and training.</li><li>
Ensure high availability, reliability, and uptime of the platform, as it is critical to the business value proposition.</li><li>
Maintain and evolve vendor-delivered platform components and ensure long-term maintainability and independence.</li><li>
Build and maintain data workflows, including tools for dataset versioning, experiment tracking, and model lifecycle management across multiple products.</li><li>
Enforce DevOps / MLOps practices, including CI/CD pipelines, Infrastructure-as-Code, and automated workflows.</li><li>
Develop cloud-agnostic and containerized solutions that can run across public and private cloud environments within EU constraints.</li><li>
Optimize data storage, lifecycle policies, and cost efficiency, including tiered storage and retention strategies.</li><li>
Implement and maintain monitoring and alerting systems (e.g., Prometheus, Grafana) for pipelines, infrastructure, and resource usage.</li><li>
Ensure data governance, security, and compliance, including access control, audit logging, and anonymization requirements.</li><li>
Collaborate closely with data scientists, ML engineers, and IT teams to deliver infrastructure that meets operational needs.</li><li>
Manage resource and cost controls, including budgets, approvals, and tracking.</li><li>
Contribute to documentation, operational runbooks, and onboarding materials for the platform.</li></ul><h4 class="jobSectionHeader">
Why Join Us?</h4><ul><li>
Join one of Europe&rsquo;s most promising deep-tech scale-ups.</li><li>
Shape the future of a rapidly growing multidisciplinary R&amp;D organization.</li><li>
Competitive salary and benefits package.</li><li>
Enjoy regular team activities and company events.</li><li>
Fresh team lunches provided3 times/ week.</li></ul><h4 class="jobSectionHeader"> 
Required Qualifications:</h4><ul><li>
MSc or equivalent with 5+ years&rsquo; industry experience in Computer Science, Data Engineering, Machine Learning, or a related field.</li><li>
Strong experience with data platforms, cloud infrastructure, and distributed systems (AWS, GCP, Azure).</li><li>
Proven experience with Infrastructure-as-Code (e.g., Terraform) and automated deployments.</li><li>
Experience with ML platforms and tools (MLflow, Feast, DVC, DataHub or equivalent).</li><li>
Experience with AWS Sagemaker or Google Vertex AI platforms.</li><li>
Experience with databases (MongoDB, PostgreSQL, InfluxDB or equivalent).</li><li>
Experience with message brokers and streaming systems (Kafka, RabbitMQ or equivalent).</li><li>
Hands-on experience with containerization (Docker/OCI) and orchestration (Kubernetes or similar).</li><li>
Experience with CI/CD systems (e.g., GitLab CI).</li><li>
Programming skills in Python.</li><li>
Experience with monitoring and observability tools (Prometheus, Grafana).</li><li>
Understanding of DevOps and MLOps practices.</li><li>
Ability to work across teams and translate requirements into scalable infrastructure solutions.</li></ul>
Nice to Have:<ul><li>
Knowledge of data governance, IAM, and security frameworks.</li><li>
Experience with cost optimization and resource management in cloud environments.</li><li>
Familiarity with multi-tenant or multi-product platform architectures.</li><li>
Experience working with EU data compliance constraints in energy, maritime or defense.</li></ul>
Security &amp; Compliance:
You'll be working with clients in the defense and security sectors, obtaining a Certificate of No Objection issued by the AIVD (Dutch General Intelligence and Security Service) is mandatory. This means you will need to undergo a security screening. For more information, please refer to details on security screening.</div>

SoTalent

<div>
 
 Data Scientist
 
 
 
 📍 Amsterdam, Netherlands | Hybrid/Flexible Working
 
 
 
 An exciting opportunity is available for a
 
 Data Scientist
 
 to develop production-ready machine learning, NLP, and Generative AI solutions that help transform complex scientific data into intelligent, real-world applications.
 
 
 Working within a collaborative, cross-functional environment, you'll design and deploy AI-powered solutions that improve knowledge discovery, information retrieval, semantic search, and decision support using large-scale scientific content and data.
 
 
 Key Responsibilities
 
 <ul>
 <li>
 Design, develop and deploy machine learning, NLP and Generative AI solutions for scientific discovery and intelligent content understanding.
 </li>
 <li>
 Build models supporting semantic search, information retrieval, recommendation systems, question answering, summarisation, entity extraction and content classification.
 </li>
 <li>
 Work with large-scale structured and unstructured datasets including scientific publications, research data, knowledge graphs, ontologies, metadata and citations.
 </li>
 <li>
 Apply a range of machine learning techniques including classification, regression, clustering, ranking, deep learning, embeddings, LLMs and retrieval-based methods.
 </li>
 <li>
 Fine-tune, evaluate and integrate AI models into scalable, production-ready systems.
 </li>
 <li>
 Develop clean, maintainable Python code and reusable data science components, pipelines and experimentation frameworks.
 </li>
 <li>
 Monitor model performance, detect drift, support automated retraining and continuously optimise deployed solutions.
 </li>
 <li>
 Partner closely with engineering, product, UX, analytics and domain experts to translate business challenges into measurable AI solutions.
 </li>
 <li>
 Communicate technical concepts, model performance and recommendations to both technical and non-technical stakeholders.
 </li>
 </ul>
 
 Skills &amp; Experience
 
 <ul>
 <li>
 Experience in Data Science, Machine Learning, Artificial Intelligence, Natural Language Processing, Statistics, Computer Science or another quantitative discipline.
 </li>
 <li>
 Strong Python programming skills with experience writing clean, well-tested and maintainable code.
 </li>
 <li>
 Experience working with Large Language Models (LLMs), including platforms such as GPT, Claude or Gemini, with exposure to prompt engineering, fine-tuning or model integration.
 </li>
 <li>
 Solid understanding of supervised and unsupervised learning, feature engineering, model evaluation and performance optimisation.
 </li>
 <li>
 Experience working with large structured, semi-structured or unstructured datasets, particularly text-heavy datasets.
 </li>
 <li>
 Proficiency with modern machine learning libraries such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch or TensorFlow.
 </li>
 <li>
 Strong analytical thinking with the ability to solve complex problems and convert ambiguous requirements into practical solutions.
 </li>
 <li>
 Excellent communication and collaboration skills with experience working across multidisciplinary teams.
 </li>
 </ul>
 
 What's on Offer
 
 <ul>
 <li>
 Flexible working arrangements supporting work-life balance.
 </li>
 <li>
 Hybrid working environment.
 </li>
 <li>
 Wellbeing initiatives, parental leave, study assistance and sabbatical opportunities.
 </li>
 <li>
 The opportunity to work on cutting-edge AI, NLP and machine learning technologies.
 </li>
 <li>
 A collaborative, innovative environment where your work contributes to advancing scientific research and healthcare worldwide.
 </li>
 <li>
 Competitive salary and comprehensive benefits package.
 </li>
 </ul>
 
 If you're passionate about applying machine learning and Generative AI to solve meaningful real-world problems while working with large-scale scientific data, this is an excellent opportunity to make a significant impact.
 
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Data Scientist

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