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data ml infrastructure engineer

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

Nebius

<div>
 
 
 Why work at Nebius
 
 
 
 
 
 
 Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.
 
 
 
 
 
 
 Where we work
 
 
 
 
 
 
 Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&amp;D hubs across Europe, North America, and Israel. The team of over 800 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&amp;D team.
 
 
 
 
 
 
 The role
 
 
 
 
 
 
 We&rsquo;re looking for a Senior Backend Software Engineer to help develop our hyperscaling platform. We have a lot of tasks on Golang and little less on Java and Python.
 
 
 You&rsquo;re welcome to work from our office in Prague, Berlin or in Amsterdam, hybrid or remotely.
 
 
 
 
 
 
 In this position, your responsibility will be to:
 
 
 
 Developing fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.
 
 
 
 
 
 
 We expect you to have:
 
 
 
 
 
 <ul>
 <li>
 5+ years of professional software engineering experience
 </li>
 <li>
 Excellent knowledge of Golang or you are ready to quickly switch to this programming language
 </li>
 <li>
 Ability to write reliable code and dig into complex problems
 </li>
 <li>
 Teamwork-oriented approach
 </li>
 </ul>
 
 
 
 
 
 It would be an added bonus if you had:
 
 
 <ul>
 <li>
 Experience designing high-load and scaling services
 </li>
 </ul>
 
 
 
 
 
 We conduct coding interviews as part of the process.
 
 
 
 
 
 
 
 What we offer
 
 
 
 
 
 <ul>
 <li>
 Competitive salary and comprehensive benefits package.
 </li>
 <li>
 Opportunities for professional growth within Nebius.
 </li>
 <li>
 Flexible working arrangements.
 </li>
 <li>
 A dynamic and collaborative work environment that values initiative and innovation.
 </li>
 </ul>
 
 
 
 
 We&rsquo;re growing and expanding our products every day. If you&rsquo;re up to the challenge and are excited about AI and ML as much as we are, join us!
 
</div>

Senior Backend Engineer

<div>
 Ben jij een Senior Machine Learning Engineer met interesse in het bouwen van Generative AI-oplossingen? Dan biedt deze rol bij KPN jou de kans om jouw AI-engineeringvaardigheden in te zetten binnen een AI-expertiseteam van Data Scientists en Machine Learning Engineers. In ons team werken we samen aan het verkennen, ontwikkelen en toepassen van de nieuwste (Gen)AI-technologie&euml;n. Je komt terecht in een jong, dynamisch team binnen het AI Excellence Center in Amsterdam, waar hybride werken, samenwerking en groeimogelijkheden centraal staan. Klaar om jouw carri&egrave;re naar een hoger niveau te tillen?
 
 
 Jouw rol als Senior Machine Learning Engineer
 
 
 In deze rol ben jij de drijvende kracht achter het ontwikkelen van nieuwe technologie&euml;n tot bouwstenen waarmee de hele organisatie GenAI-usecases kan realiseren. Je gebruikt geavanceerde software en tools om ervoor te zorgen dat deze oplossingen niet alleen werken, maar ook schaalbaar, betrouwbaar en continu beschikbaar zijn.
 
 
 Jouw dagelijkse werkzaamheden omvatten:
 
 
 <ul>
 <li>
 Ontwikkelen en onderhouden van production grade GenAI-oplossingen
 </li>
 <li>
 Prioriteiten bepalen en invloed uitoefenen op de roadmap van het GenAI Lab
 </li>
 <li>
 Operationaliseren en integreren van GenAI-technologie in bedrijfsprocessen, IT en dataplatformen
 </li>
 <li>
 Continu samenwerken met teamleden, domeinexperts en business stakeholders om de meest effectieve oplossingen te realiseren
 </li>
 <li>
 Begeleiden van junior teamleden en bijdragen aan AI Excellence
 
 
 </li>
 </ul>
 Dit is je team
 
 
 Je sluit je aan bij het jonge, enthousiaste Data Science Lab-team binnen het AI Excellence Center, bestaande uit meer dan 30 hoogopgeleide en energieke collega&rsquo;s.
 
 
 Als onderdeel van de AI-community werk je nauw samen met diverse specialisten, waaronder business stakeholders, domeinexperts, data engineers, software engineers, ML engineers, wiskundigen en data scientists.
 
 
 We hebben een hechte en groeiende AI-community van ongeveer 100 mensen uit verschillende teams en afdelingen. Elke maand organiseren we een VrijMiBo, een kennisuitwisseling en leuke activiteiten zoals padel, klimmen of pubquizzen.
 
 
 Wat breng
 
 
 jij ons?
 
 
 Je bent leergierig en flexibel, zowel technisch als persoonlijk. Je bent analytisch sterk en hebt een groot verantwoordelijkheidsgevoel. Je vindt het leuk om zowel technische als niet-technische collega&rsquo;s te betrekken bij je werk.
 
 
 Om succesvol te zijn in deze rol, breng je mee:
 
 
 <ul>
 <li>
 Minimaal 5 jaar ervaring als AI/ML Engineer of vergelijkbaar
 </li>
 <li>
 Een masterdiploma met een technische component, zoals Computer Science of Software Engineering
 </li>
 <li>
 Aantoonbare ervaring met het bouwen van production grade GenAI-applicaties (zoals RAG, Agentic AI, etc.)
 </li>
 <li>
 Ervaring met Python
 </li>
 <li>
 Ervaring met Azure en Infrastructure-as-Code
 </li>
 <li>
 Ervaring met ML-libraries, REST API&rsquo;s, microservices (Docker, Kubernetes, etc.)
 </li>
 <li>
 Uitstekende kennis van software-engineeringmethodologie&euml;n en best practices, waaronder coding standards, code reviews, versiebeheer, CI/CD, testen en security
 
 
 </li>
 </ul>
 Wat krijg je
 
 
 van ons?
 
 
 Natuurlijk hebben we als werkgever jou ook veel te bieden. Dit krijg je van ons:
 
 
 <ul>
 <li>
 Een bruto maandsalaris van minimaal &euro; 5.190 ,- en maximaal &euro; 7.803 ,- afhankelijk van je werkervaring, op basis van 40 uur exclusief 8% vakantiegeld
 </li>
 <li>
 Vaste 13e maand, een deel krijg je maandelijks uitbetaald en een deel in januari van het volgende jaar. &Oacute;f je zet het in voor een FLEX &amp; BOOST doel naar keuze! Klik hier om er meer over te lezen
 </li>
 <li>
 Jaarlijks een individuele en collectieve verhoging conform onze CAO
 </li>
 <li>
 &euro; 1500 per jaar aan inzetbaarheidsbudget dat je naar eigen inzicht mag gebruiken voor bijvoorbeeld trainingen, coaching en cursussen
 </li>
 <li>
 Flexibele vrije dagen: onze collega&rsquo;s mogen zelf (in samenspraak met de manager) bepalen hoe zij met verlof omgaan
 </li>
 <li>
 Een goede werk-priv&eacute; balans
 </li>
 <li>
 Thuiswerkshop om je werkplek thuis optimaal in te kunnen richten, uiteraard met een mobiele telefoon &amp; laptop
 </li>
 <li>
 50% korting op onze producten en diensten, zodat je voordelig kunt internetten, bellen &eacute;n streamen
 </li>
 <li>
 Goede reiskostenvergoeding: je krijgt je OV kosten volledig vergoed of &euro; 0,23 per kilometer als je met de auto reist. Kom je liever op de fiets? Dan kun je aanspraak maken op onze fietsvergoeding &euro; 0,40 per kilometer
 </li>
 <li>
 Mogelijkheid tot het aanschaffen van een leasefiets waar KPN maandelijks aan meebetaalt (bij onbepaalde tijd contract): Van stadsfiets tot e-bike en van racefiets tot speed-pedelec; jij kiest waar je op fietst
 </li>
 <li>
 Uitstekende pensioenvoorwaarden: een totale inleg van 23% van je pensioengevende salaris waarvan KPN 16% inlegt en jij 7%
 
 
 </li>
 </ul>
 Ons geloof in technologie is groot. Dit wordt n&oacute;g krachtiger samen met menselijk contact, daarom ontmoeten we je graag!
 
 
 Wil je meer weten? Neem contact op met onze recruiter Szilvia Haraszti via szilvia.haraszti@kpn.com
</div>

Senior Machine Learning Engineer

Workato

<div>
 
 About Workato
 
 
 
 Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato&rsquo;s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
 
 
 
 Why join us?
 
 
 
 Ultimately, Workato believes in fostering a
 
 flexible, trust-oriented culture that empowers everyone to take full ownership of their roles
 
 . We are driven by
 
 innovation
 
 and looking for
 
 team players
 
 who want to actively build our company.
 
 
 But, we also believe in
 
 balancing productivity with self-care
 
 . That&rsquo;s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
 
 
 If this sounds right up your alley, please submit an application. We look forward to getting to know you!
 
 
 
 Also, Feel Free To Check Out Why
 
 
 
 <ul>
 <li>
 Business Insider named us an &ldquo;enterprise startup to bet your career on&rdquo;
 </li>
 <li>
 Forbes&rsquo; Cloud 100 recognized us as one of the top 100 private cloud companies in the world
 </li>
 <li>
 Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
 </li>
 <li>
 Quartz ranked us the #1 best company for remote workers
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 We are looking for a
 
 Staff AI Engineer
 
 to play a key role in building the core of our AI platform. In this position, you will design and develop production-grade systems that power intelligent automation, agentic workflows, and large-scale retrieval services. This is a highly technical, hands-on role that involves close collaboration with product and platform teams to transform advanced AI concepts into reliable, scalable, and secure solutions used across our enterprise ecosystem. You will also be responsible to:
 
 
 <ul>
 <li>
 Design, build, and maintain AI-powered services and APIs, leveraging LLMs (OpenAI, Anthropic, Qwen, OSS models) and custom ML models.
 </li>
 <li>
 Develop an enterprise-grade agentic framework that enables orchestration, retrieval, and collaboration between multiple AI agents.
 </li>
 <li>
 Implement and optimize knowledge retrieval systems and agentic search capabilities using vector databases such as Qdrant and ElasticSearch.
 </li>
 <li>
 Write well-structured, efficient, and testable Python code for production services, experimentation, and internal developer tools.
 </li>
 <li>
 Build and maintain shared Python libraries and SDKs used across multiple applications and microservices.
 </li>
 <li>
 Collaborate with cross-functional teams on architecture, internal protocols, and API standards to ensure consistency and reliability across the platform.
 </li>
 <li>
 Develop and enhance monitoring, validation, and observability for production-grade AI solutions.
 </li>
 <li>
 Drive the full software development lifecycle - from design and implementation to deployment, monitoring, and continuous improvement.
 </li>
 <li>
 Identify and resolve performance bottlenecks, reliability issues, and scaling challenges in complex, data-intensive environments.
 </li>
 <li>
 Participate in code reviews and technical discussions, mentoring other engineers and contributing to a culture of excellence.
 
 
 </li>
 </ul>
 
 Example Projects
 
 
 
 <ul>
 <li>
 Building an evaluation and observability framework for AI model performance and reliability.
 </li>
 <li>
 Developing an agentic orchestration platform that enables collaboration among multiple AI agents and tools.
 </li>
 <li>
 Implementing semantic retrieval and agentic search capabilities over large enterprise knowledge bases.
 </li>
 <li>
 Designing AI services that process and reason over high-volume real-world data at scale.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Qualifications / Experience / Technical Skills
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
 </li>
 <li>
 5+ years of experience as a Software Engineer, with strong proficiency in Python.
 </li>
 <li>
 Proven track record of building and maintaining production-grade systems using Python.
 </li>
 <li>
 Strong understanding of distributed systems, API design, and data-driven architectures.
 </li>
 <li>
 Experience with relational and non-relational databases (PostgreSQL, Elastic, Qdrant, or similar).
 </li>
 <li>
 Familiarity with AI/ML system design, including LLM integration and evaluation pipelines.
 </li>
 <li>
 Knowledge of DevOps and observability practices (CI/CD, monitoring, metrics, and model validation).
 </li>
 <li>
 Python
 </li>
 <li>
 FastAPI
 </li>
 <li>
 LLM APIs (OpenAI, Anthropic, Qwen, OSS)
 </li>
 <li>
 LiteLLM
 </li>
 <li>
 Qdrant
 </li>
 <li>
 PostgreSQL
 </li>
 <li>
 ElasticSearch
 </li>
 <li>
 Langfuse
 </li>
 <li>
 Kubernetes
 </li>
 <li>
 GitHub Actions
 </li>
 <li>
 ArgoCD
 
 
 </li>
 </ul>
 
 Preferred Skills
 
 
 
 <ul>
 <li>
 Experience working with multiple LLM providers (OpenAI, Anthropic, Qwen, open-source models).
 </li>
 <li>
 Background in developer platforms or AI infrastructure services.
 </li>
 <li>
 Familiarity with vector databases, semantic retrieval, and knowledge graph architectures.
 </li>
 <li>
 Exposure to Langfuse, LiteLLM, LangChain, or similar frameworks.
 </li>
 <li>
 Experience developing enterprise-scale SaaS or distributed backend systems.
 </li>
 <li>
 Contributions to open-source projects in Python, AI, or infrastructure engineering.
 
 
 </li>
 </ul>
 
 Soft Skills / Personal Characteristics
 
 
 
 <ul>
 <li>
 Excellent communication skills, with the ability to convey complex technical ideas clearly to both technical and non-technical audiences.
 </li>
 <li>
 Collaborative and proactive approach, comfortable working across teams in a dynamic environment.
 </li>
 <li>
 Strong analytical and problem-solving abilities, with a focus on continuous improvement and innovation.
 </li>
 <li>
 Curiosity and a genuine interest in emerging AI technologies and modern backend architectures.
 
 
 </li>
 </ul>
 
 (REQ ID: 2460)
 
</div>

Staff AI Engineer

Sprint and Partners

<div>
 
 
 SRE - Data Platform Engineer - Kubernetes - top 0,5% biggest data set globally
 
 
 
 
 Amsterdam
 
 (Hybrid) - Visa sponsorship and relocation included
 
 
 
 
 
 Building the backbone of data &amp; AI at scale. This is not a &ldquo;keep the lights on&rdquo; role.
 
 
 
 
 
 If you are interested in:
 
 <ul>
 <li>
 Working on systems where failure is not an option
 </li>
 <li>
 A team that values engineering quality over shortcuts
 </li>
 <li>
 Real ownership &mdash; you build it, you run it, you improve it
 </li>
 <li>
 Growth paths in deep technical expertise or leadership
 </li>
 <li>
 A setup where your work has visible, measurable impact
 </li>
 </ul>
 
 
 
 
 Check this out:
 
 
 
 
 
 You&rsquo;ll be building and evolving the core platform that everything depends on&mdash;from data pipelines to machine learning and real-time AI services. Think high-scale Kubernetes, complex distributed systems, and real reliability challenges where your decisions actually matter.
 
 
 
 
 
 If you care about uptime, performance, and engineering systems that don&rsquo;t break under pressure, this is your kind of environment.
 
 
 
 
 
 Why this role stands out for SREs / Platform Engineers
 
 <ul>
 <li>
 Reliability is the product &mdash; not an afterthought
 </li>
 <li>
 Work on real-world scale problems (not toy infra)
 </li>
 <li>
 Balance batch, streaming, and real-time workloads in one platform
 </li>
 <li>
 Tackle non-trivial Kubernetes challenges (scheduling, multi-tenancy, resource isolation)
 </li>
 <li>
 Own systems that directly impact data, ML, and AI products
 </li>
 <li>
 High autonomy, high responsibility, low bureaucracy
 </li>
 </ul>
 
 
 
 
 You&rsquo;re not just supporting engineers &mdash; you&rsquo;re enabling an entire ecosystem.
 
 
 
 
 
 What you&rsquo;ll actually do
 
 <ul>
 <li>
 Build and scale Kubernetes-based platform infrastructure, keeping systems highly available under unpredictable load
 </li>
 <li>
 Drive system reliability, availability, and performance. Preventing resource contention between critical and heavy workloads
 </li>
 <li>
 Building secure, multi-tenant platforms without performance trade-offs
 </li>
 <li>
 Automate everything that shouldn&rsquo;t require human intervention
 </li>
 <li>
 Design solutions for high-throughput, data-heavy workloads. Running GPU-powered and compute-intensive workloads efficiently.
 </li>
 <li>
 Optimize scalability. Scaling storage and networking for massive data volumes. Designing smart autoscaling and cost-efficient infrastructure.
 </li>
 <li>
 Support and unblock internal teams using the platform
 </li>
 <li>
 Continuously improve observability, alerting, and incident response
 </li>
 <li>
 Be part of an on-call rotation where reliability truly matters
 </li>
 </ul>
 
 
 
 
 You:
 
 <ul>
 <li>
 Have solid experience in SRE, Platform, or Infrastructure Engineering for data platforms or big data tooling.
 </li>
 <li>
 Are comfortable with Kubernetes in production environments
 </li>
 <li>
 Understand distributed systems and failure modes
 </li>
 <li>
 Care deeply about reliability, observability, and automation
 </li>
 <li>
 Enjoy solving complex problems rather than following playbooks
 </li>
 <li>
 Exposure to high-performance workloads or GPU environments
 </li>
 </ul>
 
 
 
 
 
 Salary and benefits
 
 
 
 The base salary is between 90K and 150K euro, depending on what you bring to the table in terms of skills, personality and experience.
 
 
 Some of the secondary benefits: a permanent contract, 20% guaranteed bonus in stock, 10K+ personal allowance (can be used as extra salary), healthcare allowance (~2K a year), holiday allowance (8%), holidays, laptop, travel allowance, relocation package for Internationals, training &amp; conferences, 30% ruling, VISA sponsorship, luxury lunch, snacks/drinks, work from home setup, etc.
 
 
 
</div>

SRE - Data Platform Engineer - Kubernetes - top 0,5% biggest data set globally

KPN 

<div>Company Description 
You&rsquo;ll join in the young, enthusiastic Data Science Lab team within the AI Excellence Center of 30+ highly skilled and energetic colleagues. As part of the AI community, you&rsquo;ll work closely with various specialists, including business stakeholders, domain experts, data engineers, software engineers, ML Engineers, mathematicians, and data scientists. We have a close and thriving AI community of around ~100 people from different teams and departments with every month a VrijMiBo. Organizing every month a Knowledge exchange followed by different activities like playing padel, climbing or pubquizes. 
Job Description 
In this role, you&rsquo;re the driving force behind developing new technologies into building blocks for the whole company to build their GenAI use cases. You&rsquo;ll use cutting-edge software and tools to ensure that these solutions not only work but are also scalable, reliable, and always available. Your daily responsibilities include:<ul><li>
Developing and maintaining production-grade GenAI solutions</li><li>
Define priorities and influence the GenAI Lab roadmap.</li><li>
Operationalizing and integrating capabilities into business processes, IT, and data platforms.</li><li>
Engaging in continuous collaboration with team members, domain experts, and business stakeholders to refine and implement the most effective solutions.</li><li>
Mentoring junior team members and maintaining AI Excellence.</li></ul> 

Qualifications 
You&rsquo;re eager to learn and flexible on a technical and personal level. You&rsquo;re analytically strong and carry a strong sense of responsibility. You enjoy engaging both technical and non-technical colleagues in your work. To be successful in this role, you bring:<ul><li>
At least 5 years of experience as an AI/ML Engineer or similar.</li><li>
Master&rsquo;s degree with a technical component, like Computer Science or Software Engineering.</li><li>
Proven experience building production-grade GenAI applications (RAG, Agentic AI, etc.).</li><li>
Proficiency in Python</li><li>
Experience with Azure and Infrastructure-as-Code</li><li>
Experience with ML libraries, REST APIs, microservices (Docker, Kubernetes, etc.)</li><li>
Excellent knowledge of software engineering methodologies and best practices including coding standards, code reviews, version control, CI/CD, testing and security.</li></ul> 

Additional Information 
As an employer, we have a lot to offer you. Here&rsquo;s what you get from us:<ul><li>
A gross monthly salary starting from &euro; 5.190 to a maximum of &euro; 7.803, depending on your work experience, based on a 40-hour workweek.</li><li>
A guaranteed 13th-month salary: part of it is paid out monthly, and part in January of the following year. Or you can allocate it towards a FLEX &amp; BOOST goal of your choice! Click here to learn more.</li><li>
Annual individual and collective salary increases according to our collective labor agreement (CAO).</li><li>
&euro; 1,500 per year in a personal development budget that you can use at your discretion for training, coaching, or courses.</li><li>
Flexible leave days: our employees can (in consultation with their manager) decide how they want to handle their leave.</li><li>
A healthy work-life balance, with 2 days in the office and 3 days working from home, transition leave, and the option to swap holidays for ones that align with your religious or cultural preferences.</li><li>
A home office setup workshop to optimize your remote workspace, including a mobile phone and laptop.</li><li>
50% discount on our products and services, so you can enjoy affordable internet, calls, and streaming.</li><li>
Excellent travel reimbursement: full coverage for public transport or &euro; 0.23 per kilometer if you travel by car. Prefer cycling? You can receive &euro; 0.40 per kilometer.</li><li>
The option to purchase a lease bike co-funded by KPN (with a permanent contract): whether it&rsquo;s a city bike, e-bike, racing bike, or speed pedelec, you get to choose.</li><li>
Outstanding pension benefits: a total contribution of 23% of your pensionable salary, with KPN contributing 16% and you contributing 7%.</li></ul>
Would you like to learn more? Feel free to contact our recruiters Adumobia Rogers via E-mail at adumobia.rogers-noteboom@kpn.com
At KPN, we have recruitment talent that collaborates smartly and wins together. Unsolicited acquisition regarding this vacancy is not appreciated.</div>

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.
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