(senior) cloud infrastructure engineer - aws · gcp · azure

data scientist

machine learning engineer Jobs in Amsterdam

machine learning engineer

senior machine learning engineer Jobs in Amsterdam

senior machine learning engineer

ai builder, manager

ai engineer intern

machine learning intern

kaiko.ai

<div>
 
 About Kaiko
 
 
 
 kaiko.ai is a clinical AI research lab in Zurich and Amsterdam. We train our own large-scale frontier-class models end to end, on our own compute. The full stack is in scope, from training infrastructure and post-training algorithms to data generation, evaluation, and production inference.
 
 
 Our models are developed and deployed at leading European hospitals, and that deployment feeds back into the next training cycle.
 
 
 We're hiring interns across the lab. You'll work on the real problems of training and serving these models in a regulated clinical setting.
 
 
 
 The Opportunity
 
 
 
 As an ML Research Intern, you will be embedded in our core research team for six months, working alongside PhD researchers and senior engineers on problems that directly shape our clinical foundation model. You will own real work, contribute ideas, and see your output reflected in our system.
 
 
 Depending on your background and preferences, your project may sit in one of the following areas:
 
 
 <ul>
 <li>
 Data: Synthetic clinical data generation, multimodal data pipelines, curation and quality filtering.
 </li>
 <li>
 Evaluation: Clinical benchmarks, agentic eval design, measurement infrastructure for the production stack.
 </li>
 <li>
 Scaling: Continued pre-training on clinical corpora, post-training algorithms, distributed training at frontier scale.
 </li>
 <li>
 RL: Agentic RL on real clinical workflows, reward modeling, RL infrastructure.
 </li>
 <li>
 Acceleration: Inference &amp; Training optimisation, serving stack, quantisation and throughput tuning.
 
 
 </li>
 </ul>
 You will discuss and agree on your specific focus during the interview process, based on mutual fit and current priorities.
 
 
 
 Who You Are
 
 
 
 We are looking for MSc students or recent graduates in machine learning, computer science, or a related quantitative field. We care more about sharp thinking, high agency, and genuine curiosity than a perfect CV.
 
 
 
 You should bring:
 
 
 
 <ul>
 <li>
 Strong programming in Python and comfort with ML frameworks (PyTorch or equivalent).
 </li>
 <li>
 Hands-on experience with ML research or engineering, ideally in training, post-training, RL, data, or evaluation. Coursework, thesis, internship, or open-source all count.
 </li>
 <li>
 Clear technical communication, in design docs and in discussion with researchers, engineers, and clinical scientists.
 </li>
 <li>
 Motivation to work on hard problems with real ownership. Intern projects ship into the live training and serving stack.
 
 
 </li>
 </ul>
 The specific area depends on the project. None of these are required upfront.
 
 
 
 Why kaiko
 
 
 
 <ul>
 <li>
 Work at the frontier: you will be in the room with PhD researchers and engineers who have built production ML systems at top labs and institutions. Expect to be challenged and to grow fast.
 </li>
 <li>
 Ownership: you will set goals, make decisions, and present your findings directly to the research team, not to an intern coordinator.
 </li>
 <li>
 Conversion pathway: strong interns are actively considered for full-time roles. This is how we build the team.
 </li>
 <li>
 Fair compensation: an internship salary of CHF4000/EUR3000 gross per month
 
 
 </li>
 </ul>
 
 Interview Process
 
 
 
 We keep it fast. The process typically involves three steps:
 
 
 <ul>
 <li>
 Screening call (30 min): motivation, background, and initial fit.
 </li>
 <li>
 Technical assessment: a short, focused problem relevant to your area, reviewed together in a follow-up conversation.
 </li>
 <li>
 Onsite or video interview: meet the team, go deeper on your thinking, and align on project fit.
 
 
 </li>
 </ul>
 We review applications on a rolling basis. If you are finishing your degree this summer and want to start in September, apply now.
</div>

ML Research Graduate Internship

Amsterdam Data Collective

<div>Who we are
ADC is a Boutique Data and AI consultancy with offices in the Netherlands, Sweden, and Denmark, and an award-winning data design studio (CLEVER&deg;FRANKE) embedded in the group. We help organisations turn data and AI into real impact, leading a mission to accelerate the responsible use of Data and AI. We bring the full data value chain under one roof: from strategy and engineering to analytics, data science, and design. This way, we turn complex data into clear roadmaps, scalable foundations, AI-powered tools, and experiences people actually enjoy using.
We are a collective of statisticians, designers, PhDs, and agentic AI engineers with deep expertise in the industries we serve: financial services, life sciences, healthcare, the public sector, retail, agriculture, and transportation. We do not arrive with generic tools and a slide deck. We walk in, work alongside the people who know the organisation best, and build solutions that actually run.
We call ourselves Wayfinders. Our clients trust us to navigate complexity and make it real: turning ambition into action in environments where the margin for error is small and the consequences of getting it wrong are real, for customers, employees, supply chains, and the bottom line. 
Shape the future of Data-Driven Decision Making with ADC
We're leveraging our expertise in causal inference, machine learning, and business intelligence to power ADC's growth and deliver unmatched value to our clients.
Our Retail team is growing, and we are looking for a Decision Scientist with experience with ML and forecasting, who is curious and eager to grow with us. In this role, you will deep dive into predictive modelling, causal inference, and optimization, while applying advanced statistical methods to real-world business challenges. You will contribute to our advanced pricing initiatives for leading e‑commerce clients, developing forecasting models that impact commercial strategy.
You&rsquo;ll be part of cross-functional team, working alongside highly specialized decision science teams to better understand complex methodologies, while connecting predictive insights with operations research, and deploying state-of-the-art causal machine learning techniques. 
Where you&rsquo;ll make an impact
Turn Advanced Machine Learning into Real‑World Pricing Impact<ul><li>
Drive advanced forecasting for e‑commerce pricing, focusing on longitudinal and panel data.</li><li>
Develop and scale Machine Learning models to optimize pricing strategies over time.</li><li>
Leverage techniques such as tree‑based models, gradient boosting, bagging, and ensemble methods (e.g. LightGBM, XGBoost) to improve pricing performance.</li></ul>
Use Causal Inference to Measure True Business Impact<ul><li>
Drive causal machine learning and inference initiatives to move beyond correlation and quantify true commercial impact.</li><li>
Apply causal inference methods to observational and quasi‑experimental data to support strategic decision‑making.</li><li>
Implement advanced frameworks such as DoubleML, potential outcomes modeling, two‑way and interactive fixed‑effects models, and unobserved factor models.</li></ul>
Collaborate with Expert Teams and Drive Continuous Improvement<ul><li>
Collaborate closely with our clients' decision science teams, highly specialized professionals with deep quantitative backgrounds, tackling complex methodologies and operations research challenges together.</li><li>
Break down data science and econometric concepts into clear, practical recommendations that resonate with both technical and non‑technical audiences.</li><li>
Challenge existing approaches, identify opportunities for stronger models or smarter optimization, and foster a mindset of curiosity, transparency, and continuous improvement across the team.</li></ul> 
What you bring
At ADC, we're not just consultants: we're leading experts in Data &amp; AI, using our expertise in strategy, business operations, and advanced analytics. What unites us is a shared way of working: breaking down complex challenges to change how organisations operate.
For this role, that means:<ul><li>
Strong academic foundation in Machine Learning, Computer Science, Statistics, Econometrics, Economics, Mathematics, or a highly related quantitative field, ideally in consulting or project-based work.</li><li>
Deep technical expertise: Hands-on experience in Machine Learning methods for forecasting longitudinal data (LightGBM, XGBoost, ensemble methods) and causal machine learning / causal inference methods (DoubleML, fixed effects models, potential outcomes).</li><li>
Domain knowledge: Experience applying forecasting, optimization (operations research), and causal inference specifically for pricing in retail and e-commerce settings is particularly desirable.</li><li>
The ability to communicate with anyone in the room breaking down complex ideas for technical and non-technical audiences: From client PhD researchers to commercial leadership.</li><li>
A proactive and entrepreneurial mindset: You&rsquo;re eager to solve challenging problems, innovate, and drive change.</li><li>
A collaborative spirit: You believe the best solutions come from diverse perspectives and supporting each other to raise the bar.</li><li>
Fluency in English; Dutch is a plus.</li></ul> 
What&rsquo;s in it for you
At ADC, you&rsquo;re part of the collective from day one. We want you to grow, experiment, and shape your own path while working on projects that matter. That means:<ul><li>
Impact you can point to: You&rsquo;ll see your work in action and our projects change how organisations make decisions.</li><li>
Real responsibility, real support: You&rsquo;ll work alongside experienced experts from the start, learning by doing with mentorship and feedback built in.</li><li>
The freedom to try new things: Spot a better way to build something? A smarter process? We want people who challenge the status quo.</li><li>
Collective Week: Once a year, we go on a workation with the whole ADC team. We work on pro bono projects, explore new ideas, and make the kind of memories you&rsquo;ll want to talk about.</li><li>
Ownership opportunities: We offer a competitive salary and bonus structure, plus the opportunity to invest in the company and become a co-owner once specific conditions are met. We mean it when we say collective.</li><li>
A vibrant culture: Daily lunches, Friday drinks, sports, social events: a culture you&rsquo;ll notice from day one.</li></ul>
What to do next
If you believe in building with heart, thrive on collaboration, and want to grow with a team that challenges and supports you, we want to meet you! If this sounds like your next challenge, apply through the link below.<ul><li>Amsterdam Data Collective is an equal opportunity employer. To shape a better future, we value diversity and promote equality. No characteristics are discriminated against, as indicated in Directive 2000/78/EC. We encourage and welcome all applications. Additional arrangements or adjustments to support your application can be discussed further.</li></ul></div>

Machine Learning Scientist | Pricing & Forecasting

Xomnia

<div>
 
 About The Role And The Xomnia Culture
 
 
 
 At Xomnia, machine learning is more than model building - it&rsquo;s about engineering intelligent systems that deliver real value. As a Machine Learning Engineer, you&rsquo;ll work alongside passionate consultants to help our clients unlock the full potential of their data.
 
 
 From advancing cancer research to real-time fraud detection and electricity grid optimization, we work on projects that make a difference. Our culture thrives on curiosity, shared ownership, and the courage to challenge assumptions. We value people who enjoy experimenting, sharing knowledge, and working together to create AI solutions that last.
 
 
 
 Are you ready to take on this challenge?
 
 
 
 In this role, you&rsquo;ll develop and deploy machine learning models across diverse domains - from healthcare to logistics and finance. Whether you&rsquo;re designing recommender systems, deploying models to the cloud, or helping clients adopt MLOps practices, your consultancy skills will bring together technical excellence and business impact.
 
 
 
 Your role
 
 
 
 <ul>
 <li>
 Design and implement robust ML models that solve real-world problems.
 </li>
 <li>
 Build end-to-end ML pipelines - from feature engineering to deployment and monitoring.
 </li>
 <li>
 Collaborate with cross-functional teams to turn business needs into scalable solutions.
 </li>
 <li>
 Apply MLOps best practices such as CI/CD, versioning, testing, and automation.
 </li>
 <li>
 Deploy models on cloud platforms like Azure, AWS, or GCP.
 </li>
 <li>
 Work with tools like MLflow, Airflow, Docker, Kubernetes, and Spark.
 </li>
 <li>
 Stay up to date with the latest techniques, including Generative AI, and explore their application.
 </li>
 <li>
 Guide clients in building internal ML capabilities and following engineering best practices.
 </li>
 <li>
 Share your expertise through mentorship, demos, and internal learning sessions.
 
 
 </li>
 </ul>
 
 What You Bring To The Table
 
 
 
 <ul>
 <li>
 Preferable +/- 2-5 years of relevant experience in ML engineering, data science, or similar roles.
 </li>
 <li>
 A degree in Computer Science, AI, Data Science, or a related technical field.
 </li>
 <li>
 Strong coding skills in Python and experience with cloud environments (Azure, AWS, or GCP).
 </li>
 <li>
 Solid understanding of statistics and machine learning fundamentals.
 </li>
 <li>
 Experience building and deploying production-grade ML systems.
 </li>
 <li>
 Familiarity with Docker, CI/CD pipelines, infrastructure-as-code, and orchestration tools.
 </li>
 <li>
 A consulting mindset: you enjoy listening, collaborating, and turning needs into solutions.
 </li>
 <li>
 Fluent in English and Dutch.
 </li>
 <li>
 A drive to learn, improve, and share knowledge - both internally and with the broader tech community.
 
 
 </li>
 </ul>
 
 What&rsquo;s in it for you?
 
 
 
 We offer more than a job - we offer a platform for growth:
 
 
 <ul>
 <li>
 A monthly salary between &euro;3.800 - &euro;6.200 per month (based on 40 hours and excluding vacation allowance)
 </li>
 <li>
 &euro;5.000 annual development budget
 </li>
 <li>
 25 vacation days to fully recharge
 </li>
 <li>
 Secondary benefits such as pension, flexible working options (in terms working location) and the possibility to take unpaid leave
 </li>
 <li>
 Memorable company trips (Berlin this year!)
 </li>
 <li>
 The opportunity to grow along with our success through Stock Appreciation Rights
 
 
 </li>
 </ul>
 At Xomnia, we believe that collaboration, knowledge sharing, and personal development are the keys to our success. That&rsquo;s why we offer various trainings through our &lsquo;Learning Labs&rsquo; and organize a yearly Health Month. We also regularly enjoy boat trips through the Amsterdam canals with our own boat, and there is always a healthy (free) lunch and a bar at the office.
 
 
 
 Become a Xomnian!
 
 
 
 At Xomnia, we believe in using data and AI to tackle real-world challenges. With a team of passionate experts from 20+ nationalities and over 30% female representation, we celebrate diversity and welcome different perspectives.
 
 
 
 We Are Proud Of Our Core Values
 
 
 
 
 We are challengers
 
 ,
 
 we embrace agility
 
 , and
 
 we always share
 
 .
 
 
 Want to be part of this and take the next step in your career?
 
 
 
 Apply now or reach out to ezra.lammers@xomnia.com. We look forward to meeting you.
 
</div>

Machine Learning Engineer

<div>Company Description 
Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We&rsquo;re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes. 
Job Description 
What you will do 
As an expert in the field of Machine Learning Engineering you will be responsible for the growth of our Data team, both professionally as well as in size. You will be in charge of shaping and executing the future of your expertise within Sia. You will work on client projects as well as on building our own Sia AI solutions, together with our Dutch team of Data Scientists, our French Data Engineering team, and other business units of Sia Global.
Your responsibilities include:<ul><li>
Leading an internal team towards the development of AI products;</li><li>
Working in a multidisciplinary team on client projects as an expert on your subject;</li><li>
Making architectural and design decisions for cloud environments;</li><li>
Building production level ML/AI solutions with solid software engineering;</li><li>
Guiding Data Scientists to scale up their models into production (parallelizing, optimizing, tuning, testing, and wrapping);</li><li>
Giving trainings, leading internal meetings and organizing external events;</li><li>
Participating in team meetings and workshops with clients;</li><li>
Writing blog articles, presenting at conferences and sending out press releases on the subject that you lead.</li></ul>
Who you will work with 
The Data Science team is young, diverse and growing (10+). You will join a team that will challenge you and invest in your professional development. We have a flat structure and rely on the entrepreneurial spirit of our members: initiative is highly encouraged. We are striving for well-being, diversity and knowledge-sharing inside the team, so that we can grow together.
Who you are<ul><li>
You are an established technical professional that wants to make the next step in their career, taking on more leadership responsibilities.</li><li>
You have first-rate project management and time management skills.</li><li>
You are a true problem solver, you turn complex issues into simple and impactful business solutions.</li><li>
You are enthusiastic for applying Data Science/Engineering solutions to business problems.</li><li>
You have excellent communication skills and can present complicated concepts in a synthetic way.</li><li>
You have the ability to adapt rapidly and work on a range of different business areas within a challenging environment.</li><li>
You have the ability to work collaboratively in a team environment.</li></ul>
In return, you can expect:<ul><li>
An international company that gives importance to diversity, inclusion, employee well-being and corporate social responsibilities actions.</li><li>
A great working atmosphere with friendly and professional colleagues where innovation and entrepreneurship are encouraged</li><li>
A personal development plan with a regular follow-up as well training opportunities to develop yourself</li><li>
A competitive salary with great advantages, like mobility budget, hospital insurance, performance -related bonus,...</li></ul> 

Qualifications 
<ul><li>
MSc level education in Computer Science, Applied Mathematics, Artificial Intelligence, Embedded Systems or related field of study.</li><li>
2-4 years of experience in building production-quality ML/Deep Learning pipelines and models.</li><li>
Good understanding of Machine Learning fundamentals and strong knowledge in a specific domain (e.g., Computer Vision, Deep Learning, NLP).</li><li>
Expert coding skills in Python and at least one of these languages: Scala, C++, Java.</li><li>
Hands-on experience with database management languages (e.g., SQL, PostgreSQL).</li><li>
Hands-on experience in cloud-based infrastructures (AWS/GCP/Azure).</li><li>
Hands-on experience with Unix-based command line and DevOps tools (Git, Docker, Kubernetes).</li><li>
Hands-on experience with big data technologies (e.g. Spark, Hadoop, Databricks).</li><li>
You have a strong interest in data and AI-related topics, the ability to quickly build expertise in these areas, and you&rsquo;re excited about helping our clients seize the opportunities they offer.</li><li>
Experience with coaching/mentoring other engineers.</li><li>
Prior experience in Management Consulting is a strong plus.</li><li>
Willingness to travel and work at local and international clients.</li><li>
Fluency in spoken and written English and Dutch is required.</li></ul> 

Additional Information 
We are unable to provide a work permit for this position
Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.<div></div>
Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.</div>

Machine learning Engineer

reddit

<div><div><div><div><div><div><div><div>Reddit is a community of communities. It's built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet's largest sources of information. For more information, visit www.redditinc.com.</div>
</div>
</div></div></div></div></div>Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands.

About the Team

The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company's ML ecosystem.

Responsibilities
<ul>
<li>Design and build systems that improve the efficiency of ML training and inference workloads.</li>
<li>Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.</li>
<li>Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization.</li>
<li>Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.</li>
<li>Build benchmarking frameworks and performance dashboards for training and serving systems.</li>
<li>Optimize distributed training infrastructure, data pipelines, and model serving architectures.</li>
<li>Lead cross-functional initiatives that improve the productivity of Reddit ML engineers.</li>
<li>Drive technical strategy for ML platform scalability, reliability, and cost efficiency.</li>
</ul>
Qualifications

Required
<ul>
<li>BS, MS, or PhD in Computer Science or a related field.</li>
<li>5+ years of software engineering experience.</li>
<li>Strong proficiency in Python</li>
<li>Profiency in at least one systems language (Go, C++, Rust, or Java) preferred</li>
<li>Experience building distributed systems at scale.</li>
<li>Experience with machine learning infrastructure, training systems, or model serving platforms.</li>
<li>Deep understanding of performance engineering and systems optimization.</li>
<li>Strong debugging and profiling skills.</li>
</ul>
Preferred
<ul>
<li>Experience with large-scale recommendation, ranking, generative AI, or foundation model systems.</li>
<li>Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark</li>
<li>Familiarity with GPU architectures and performance analysis tools.</li>
<li>Experience optimizing cloud infrastructure costs across large ML workloads.</li>
<li>Contributions to internal platforms used by multiple ML teams.</li>
<li>Experience with building real time ML inference applications</li>
</ul>
What Success Looks Like
<ul>
<li>ML engineers can move from idea to experiment faster.</li>
<li>Training and inference costs decrease, performance increases, while model quality is maintained or improved.</li>
<li>GPU utilization and cluster efficiency increase.</li>
<li>Platform reliability improves as ML workloads scale.</li>
<li>Teams spend less time managing infrastructure and more time building models.</li>
<li>Average recommendation model size increases.</li>
</ul>
Benefits:
<ul>
<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>
<li>Family Planning Support</li>
<li>Gender-Affirming Care</li>
<li>Mental Health &amp; Coaching Benefits</li>
<li>Private Pension plan with Employer-matching</li>
<li>100% employer-sponsored group medical plan</li>
<li>Income Replacement Programs</li>
<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>
<li>Generous Paid Parental Leave</li>
</ul><div>
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.</div></div>

Staff Machine Learning Engineer, ML Efficiency

ABN AMRO Bank N.V.

<div>
 
 At a glance
 
 
 
 The Finance and Risk Data Domain is looking for an experienced (8+ years) machine learning engineer for the advanced analytics and AI team. The position is for 40 hours per week at hay level 11 (&euro; 70.000- &euro; 100.000 yearly gross based on 40 hrs) and you would join around 10 other engineers to create AI driven solutions that empower our business.
 
 
 The AI team uses its expertise to turn promising (gen)AI ideas into fully fledged products. These products are data driven and assist the business in unlocking the full value of our data in order to make better informed decisions. Several applications are already in use and are used daily by colleagues across the organization.
 
 
 
 Your job
 
 
 
 Your role within this team will include the design and creation of AI models/applications. You will also be expected to be able to explain the value of your designs and defend the choices made. As an expert and frontrunner on AI you should also be able to convince others of the value that your applications can bring, as well as coach and train less experienced engineers in the proper use of AI.
 
 
 AI applications usually start their journey with a business requirement and an idea to have AI assist with the stated problem. Then a proof of concept phase starts, followed by a formal production design and implementation if successful. You will be involved at all stages of this pipeline, offering advice and guidance, and aiding with the design and implementation, either directly or indirectly. You will also train teams to maintain these applications.
 
 
 
 Your profile
 
 
 
 We heavily utilize Databricks in our environment for our data applications, using Python as our language of choice. Required skills would therefore include:
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Spark/PySpark
 </li>
 <li>
 Databricks
 </li>
 <li>
 Azure (AI services especially)
 </li>
 <li>
 SQL
 </li>
 <li>
 Software development practices (clean code, SOLID, patterns etc.)
 </li>
 <li>
 Excellent communication and stakeholder management skills
 
 
 
 </li>
 </ul>
 AI-Assisted Development (nice to have)
 
 
 <ul>
 <li>
 Experience with AI-assisted development tools (e.g. GitHub Copilot in VS Code / IDEs)
 </li>
 <li>
 Able to establish and maintain structured AI context (e.g. repository-level instructions, prompts, and reusable skills)
 </li>
 <li>
 Guides AI tools by embedding team standards, architectural decisions, and best practices into reusable context
 </li>
 <li>
 Reduces rework and inconsistency by contributing to shared AI assets (templates, examples, and patterns)
 </li>
 <li>
 Critically evaluates AI-generated output and ensures alignment with quality, security, and maintainability expectationsIdentifies opportunities to scale AI usage across the team through structured approaches rather than ad-hoc prompting
 
 
 
 </li>
 </ul>
 
 Working environment
 
 
 
 The F&amp;R data domain is a multicultural environment that works in an agile way and promotes knowledge sharing and collaboration. We host department wide sessions several times a year to facilitate this and have some fun events on top.
 
 
 
 We are offering
 
 
 
 We believe it is important to be a good employer. Joining us means stepping into a role with impact, supported by excellent employment conditions that foster your job satisfaction, development, and wellbeing.
 
 
 In addition, we offer:
 
 
 <ul>
 <li>
 An attractive gross monthly salary based on a 36‑hour work week, including holiday allowance and a flexible benefit budget.
 </li>
 <li>
 An excellent pension scheme, ensuring that you are well prepared for the future.
 </li>
 <li>
 Flexibility in working: working from home is possible in consultation with your team and depending on your role. We will provide an ergonomic home office setup for you.
 </li>
 <li>
 Plenty of room for relaxation with five weeks of vacation per year, supplemented by two mandatory days off. You can also purchase up to four additional weeks of vacation annually.
 </li>
 <li>
 Five &ldquo;Banking for better days&rdquo;: extra days off that you can use for personal development or volunteer work.
 </li>
 <li>
 Personal development is key: you receive a development budget of &euro;1,000 per year, which can accumulate up to &euro;3,000.
 </li>
 <li>
 An annual public transport pass with free public transportation throughout the Netherlands for both business and private use.
 
 
 
 </li>
 </ul>
 You can find more information about our employment conditions and salary scales in our Collective Labour Agreement (CLA), which applies to this vacancy.
 
 
 
 Interested?
 
 
 
 After initial screening, the interview process consists of a first interview to go over the role and relevant experience and skills in broad strokes. This is followed by a technical assignment and a technical interview. The assignment covers the basic aspects of the job and forms a starting point for the second interview. After the second interview we will usually take a decision, although on rare occasions a third interview can take place. For additional questions, you can contact the hiring manager: jasper.ris@nl.abnamro.com
 
 
 
 Your Future: Inclusive, Innovative, Sustainable
 
 
 
 At ABN AMRO, we believe in "Banking for better, for generations to come." Equal opportunities for everyone are a crucial foundation, as we strive for an inclusive culture where all employees feel seen, heard, and valued. Our vision of being a personal bank in the digital age aligns perfectly with the demand for surprising insights and innovative solutions, born from a diverse interplay of cultures and experiences. We focus on customer experience, sustainability, and building a future-proof bank, conducting annual reviews to ensure equal pay for equal work. Join a bank that embraces ingenuity and ambition, and make an impact with us for a better future.
 
 
 If you want to apply for the B-Able or Reboot program, make sure to mention it both in the title and the content of your resume.
 
 
 
 Disclaimer external recruitment agencies
 
 
 
 External recruitment agencies need to have a signed agreement with ABN AMRO BANK N.V., executed by a Talent Acquisition Specialist, when submitting a resume to a vacancy. No unsolicited services or offers, please.
</div>

Machine Learning & AI Engineer

GAIDE

About GaideGaide is the strategic AI partner for SMB+. We help organizations unlock the value of AI step by step - from defining a clear AI strategy and building AI literacy to full implementation. Together with our clients, we build human-centered, AI-driven organizations, where AI becomes embedded in the DNA of core business activities.As an intern, you won&rsquo;t just observe this journey - you&rsquo;ll help apply and scale AI from within Gaide itself.What will you do?As an AI Engineer Intern, you will work hands-on on applying AI inside Gaide. You&rsquo;ll be embedded across teams and work closely with AI consultants and AI engineers, learning how AI solutions are designed, built, and deployed in practice.Your focus is on shipping real internal AI solutions, primarily using low-code / no-code tools, while gradually deepening your technical understanding.Your responsibilities include:<ul><li>Working alongside AI consultants to identify and shape internal AI use cases</li><li>Translating business and operational needs into practical AI-powered workflows</li><li>Designing and building low-code / no-code AI automations and agents for internal teams</li><li>Supporting internal AI projects from idea through deployment and iteration</li><li>Testing, improving, and maintaining deployed internal AI solutions</li><li>Learning how AI engineers approach architecture, integration, and reliability</li><li>Acting as a bridge between business context and technical implementation</li><li>This is a forward-deployed role: you don&rsquo;t wait for perfect specs - you iterate, deploy, learn, and improve.</li></ul>What you bring<ul><li>You are currently enrolled in a Bachelor&rsquo;s or Master&rsquo;s program (e.g. Computer Science, AI, Data Science, Business Analytics, or related)</li><li>You are comfortable working with low-code / no-code tools, prompts, and automations</li><li>You have a strong interest in AI systems and how they are used in real organizations</li><li>You are curious, proactive, and enjoy learning from experienced practitioners</li><li>You can work independently, take ownership, and communicate clearly</li><li>You enjoy improving workflows and making systems more effective</li><li>You are comfortable in a fast-paced startup environment</li></ul>You don&rsquo;t need deep engineering expertise - learning mindset and execution matter most!What we offer<ul><li>A paid, hands-on internship with real ownership and visible impact</li><li>Minimum 3 days per week, flexible around your studies</li><li>Daily exposure to how AI consultants and AI engineers work in practice</li><li>Strong learning curve across consulting, product thinking, and applied AI</li><li>Hybrid setup: working from our Keizersgracht office in Amsterdam and remotely</li><li>A strong opportunity to continue at Gaide after the internship (working-student role or permanent position), depending on mutual fit</li><li>An ambitious team that values initiative, pragmatism, and growth</li></ul>How to applyInterested? Let&rsquo;s talk.Apply through this link: https://forms.clickup.com/9012069442/f/8cjjh22-55212/IOAGVMZA64CKZD1F4KJob Types: Part-time, Internship Contract length: 5-6 monthsWork Location: Hybrid remote in 1016 Amsterdam Centrum

AI Engineer Intern

Explore 60+ Machine learning intern in Amsterdam this July. Find roles across top companies and apply now to boost your career.