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data & ml infrastructure engineer Jobs in Amsterdam

data & ml infrastructure engineer

data 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

<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>

Angi

<div>For over 30 years, Angi has powered the future of the home services industry, creating an environment where homeowners and pros benefit from more jobs done well.
For homeowners, our platform is a reliable way to find skilled pros. For pros, we're a reliable business partner who helps them find the winnable work they want, when they want. For employees, we're an amazing place to call home. We can't wait to welcome you.
Angi at a glance:<ul><li>
Founded in 1995 as Angie&rsquo;s List and rebranded in 2021</li><li>
Global company with 9 brands in 8 countries and employees worldwide</li><li>
Homeowners have turned to us for 300 million home projects and counting</li></ul>
About the team:
Angi is seeking a Senior Engineer I to join our Data Infrastructure team, responsible for building and operating the foundational platforms that power data processing, storage, and analytics across the organization. This role will focus on evolving our lakehouse architecture, data replication systems, and orchestration frameworks while enabling scalable, reliable, and efficient data workflows.
What You'll Do:<ul><li>
Design, build, and operate critical data infrastructure platforms (lakehouse, replication, orchestration, and distributed compute)</li><li>
Ensure high availability, scalability, and performance of platform services supporting enterprise data workloads</li><li>
Contribute to infrastructure architecture decisions aligned with large-scale, modern data platform standards</li><li>
Partner closely with engineering, analytics, and product teams to support data platform adoption and migration initiatives</li><li>
Drive improvements in developer productivity through automation, tooling, and AI/agentic workflows</li><li>
Participate in on-call rotations and lead troubleshooting efforts for complex production issues</li><li>
Produce clear, comprehensive documentation and operational runbooks to support platform usage and reliability</li></ul>
Who You Are:<ul><li>
5+ years of experience in infrastructure, platform engineering, or data engineering roles</li><li>
Experience working on highly cohesive engineering teams that collaborate in real time to solve complex technical challenges</li><li>
Strong background in infrastructure architecture within large-scale or enterprise environments</li><li>
Hands-on experience with cloud platforms (e.g., Amazon Web Services), container orchestration (e.g., Kubernetes), and distributed systems</li><li>
Extensive experience with end-to-end Kubernetes management, including cluster provisioning, lifecycle management, and observability</li><li>
Strong proficiency with Infrastructure as Code (IaC) principles and tools (e.g., Terraform, crossplane, or Pulumi) to automate and manage cloud environments</li><li>
Proven experience self-hosting and managing core infrastructure and open-source tools as an alternative to using commercial managed services</li><li>
Experience with data platforms, including lakehouse architectures, data replication, and orchestration frameworks (e.g., Airflow, Kafka, Trino, Iceberg)</li><li>
Demonstrated experience using AI/agentic engineering tools such as Claude Code, Cursor, GitHub Copilot, or similar tools to improve development efficiency and workflows</li><li>
Demonstrated ability to pivot quickly in response to changing priorities while maintaining high-quality delivery</li><li>
Strong communication skills with the ability to clearly articulate technical concepts and tradeoffs to stakeholders</li><li>
Proven ability to collaborate cross-functionally and engage effectively with both technical and non-technical partners</li><li>
Track record of producing clear, high-quality documentation and enabling others through shared knowledge</li><li>
Mindset of an enabler&mdash;focused not only on building systems, but on empowering other teams to use them effectively</li></ul>
Compensation &amp; Benefits<ul><li>
The salary band for this position ranges from &euro;85,000 - &euro;115,000, commensurate with experience and qualifications.</li><li>
Hybrid work environment and home office set-up allowance</li><li>
Temporary work from abroad policy</li><li>
Regular team and social events</li></ul></div>

Senior Engineer, Data Infrastructure

CuspAI

<div>
 
 About CuspAI
 
 
 
 CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering.
 
 
 We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock.
 
 
 We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters.
 
 
 
 We&rsquo;re on the cusp of the on-demand materials era. Join us.
 
 
 
 
 The Role
 
 
 
 As we grow, we are seeking a
 
 Data Engineer
 
 to play a crucial part in driving our research and development efforts forward.
 
 
 
 Your Impact
 
 
 
 As a Data Engineer you will be part of the new team building the infrastructure that underpins and acts as the critical bridge between raw chemical data and our machine learning models.
 
 
 
 Your main focus will be to build the pipeline infrastructure and tooling for data ingestion, moving towards self-serve setup for the scientific team members
 
 . You'll also be responsible for securing, collecting, cleaning, standardising, and tagging diverse chemical datasets to create high-quality training data for our ML researchers while working closely with our chemistry team to ensure scientific accuracy.
 
 
 
 What You Will Do
 
 
 
 
 Data Pipeline Development
 
 
 
 <ul>
 <li>
 Design and build robust data pipelines for materials science datasets, experimental results, and computational chemistry outputs.
 </li>
 <li>
 Develop processes to integrate diverse data sources including materials databases, literature, patent filings, and laboratory instruments.
 </li>
 <li>
 Create automated workflows for processing crystallographic data, molecular structures, and materials properties (you don&rsquo;t need to have direct domain experience - we can help bring you up to speed!).
 </li>
 <li>
 Build scalable systems to handle high-throughput computational chemistry calculations and experimental data.
 
 
 </li>
 </ul>
 
 Data Quality &amp; Standardisation
 
 
 
 <ul>
 <li>
 Partner closely with the scientific and research teams to implement automated quality checks for crystal structure data, chemical compositions, and experimental measurements.
 </li>
 <li>
 Create standardisation protocols for materials nomenclature, units, and measurement conditions.
 </li>
 <li>
 Build monitoring systems to ensure data integrity across all pipelines.
 
 
 </li>
 </ul>
 
 Collaboration &amp; Integration
 
 
 
 <ul>
 <li>
 You will also be working hand in hand with ML researchers to understand data requirements for model training and inference.
 </li>
 <li>
 Partner with materials scientists to ensure accurate representation of domain knowledge in data schemas.
 </li>
 <li>
 Integrate with laboratory automation systems and computational chemistry software.
 </li>
 <li>
 Support real-time data needs for AI-driven materials discovery experiments.
 
 
 </li>
 </ul>
 
 Must Have Skills and Qualifications
 
 
 
 <ul>
 <li>
 You are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that Cusp is building.
 </li>
 <li>
 You&rsquo;re a builder of tools and infrastructure who enjoys making life as easy as possible for the teams, providing self-serve, reliable and scalable ingestion pipelines.
 </li>
 <li>
 You have at least 3+ years experience in data engineering roles, preferably in scientific or research environments - you would be joining as a data engineering subject matter expert who can not only work autonomously but also provide guidance on best practice.
 </li>
 <li>
 High level of proficiency in Python and databases with experience in large-scale data processing - as part of our engineering team you&rsquo;ll be programming regularly, not just scripting.
 </li>
 <li>
 You&rsquo;re an advanced user of workflow orchestration tools (e.g. Airflow, Prefect, Dagster, Flyte or similar).
 </li>
 <li>
 Solid experience with containerisation (Docker, Kubernetes) and CI/CD practices.
 </li>
 <li>
 You have direct experience handling large/complex datasets and are interested in working with scientific packages.
 </li>
 <li>
 You&rsquo;re a fast learner when it comes to new tools/systems.
 </li>
 <li>
 You enjoy (and have experience in) designing systems that scale with growing data volumes and user demands.
 </li>
 <li>
 Understanding and appreciation of DevOps practices is also important.
 
 
 </li>
 </ul>
 
 Bonus Points (But Not Critical)
 
 
 
 <ul>
 <li>
 You&rsquo;ve worked with data from scientific computing (simulations or experiments).
 </li>
 <li>
 Knowledge of machine learning data requirements and MLOps practices, including pre-processing/processing as part of model training.
 </li>
 <li>
 An academic background in Materials Science, Chemistry, Chemical Engineering, or related field.
 
 
 </li>
 </ul>
 Even more bonus points if you have an understanding of crystallography, materials properties, and computational chemistry concepts!
 
 
 
 What we offer
 
 
 
 <ul>
 <li>
 A competitive salary: We value and reward impact and growth
 </li>
 <li>
 Equity in CuspAI: You have a stake in the success of the company
 </li>
 <li>
 Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays
 </li>
 <li>
 &lsquo;Gold Standard&rsquo; parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together
 </li>
 <li>
 Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth
 </li>
 <li>
 Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate-related problems through the creation and application of bleeding-edge SOTA technology and revolutionary techniques
 </li>
 <li>
 True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world-class researchers and engineers who enjoy sharing knowledge and supporting each other
 
 
 </li>
 </ul>
 
 Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world.
 
 
 
 
 CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace
 
 . We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law.
 
 
 
 We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team.
 
 
 
 
 Please let us know If you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.
 
 
 
</div>

Data Engineer

Xomnia

<div><h3 class="jobSectionHeader">Senior Data Platform Engineer</h3>
At Xomnia, Senior Data Platform Engineers don't just build systems. They define how data platforms evolve. As a Senior Data Platform Engineer, you will set the architectural direction that enables organizations like KLM, Enexis, and Rabobank to operate at the frontier of data and AI. 
 
You build with conviction: shaping standards, steering technical trade-offs, and leaving a lasting mark on both client platforms and the broader engineering culture at Xomnia.<h3 class="jobSectionHeader">
Lead architecture that others build on</h3>
Joining Xomnia means entering a community of over 20 nationalities driven by one shared ambition: using data and AI to solve problems that actually matter. At senior level, that ambition takes on a different weight. You are not just executing, you are setting direction. The Xomnia way rewards engineers who challenge assumptions, share knowledge generously, and raise the bar for everyone around them.
As a Senior Data Platform Engineer, your growth trajectory leans into ownership. You'll drive architectural decisions, act as a trusted technical advisor to clients, and mentor the engineers coming up behind you. Dedicated internal time gives you space to explore new technologies and contribute to the standards that define how Xomnia builds.<h3 class="jobSectionHeader">
What the role looks like in practice</h3>
Your week moves between our Amsterdam HQ on Raamstraat with its canal views, uneven floors, and the kind of Friday design sessions that actually move things forward, client environments, and home. At senior level, you're as likely to be leading a migration architecture discussion as you are optimizing a pipeline that processes millions of records overnight.
Some examples of the type of work we do: a cloud platform overhaul at a.s.r, a data infrastructure project at DAF, and an end-to-end solution at Albert Heijn.<h3 class="jobSectionHeader"> 
What you bring to the table</h3>
You've moved past proving you can build; now you're focused on building the right things, the right way, and bringing others along with you. What we're looking for:<ul><li>
5+ years in data engineering or data-intensive backend systems, with end-to-end ownership of production-grade platforms.</li><li>
You translate technical depth into clear direction for engineers, clients, and stakeholders.</li><li>
Proven experience designing scalable cloud architectures and leading the technical discussions that drive decisions.</li><li>
Deep expertise optimizing pipelines for performance, reliability, and cost, at a scale where it matters.</li><li>
An excellent understanding of technology trade-offs in data platforms specific to a wide range of different use cases.</li><li>
Proficiency with Infrastructure as Code (e.g., Terraform) and CI/CD-driven data workflows.</li><li>
Fluent in English; Dutch is a strong plus.</li><li>
Eligible to work in the Netherlands.</li></ul><h3 class="jobSectionHeader">
What's in it for you?</h3>
Xomnia invests in the people who push things forward. For Senior Data Platform Engineers, that looks like this:<ul><li>
A monthly salary between &euro;5,650 &ndash; &euro;6,800 (based on 40 hours, excluding vacation allowance), plus Stock Appreciation Rights to share in what we're building together.</li><li>
A dedicated &euro;5,000 annual development budget, access to Learning Labs, and real internal influence over how Xomnia engineers.</li><li>
25 vacation days, with the option for unpaid leave or the occasional stint working from abroad.</li><li>
Company trips that range from ski slopes to Jordan, regular canal boat rides, and a Raamstraat office stocked with healthy lunches and a fully loaded bar, every day.</li><li>
A solid pension scheme and flexible working arrangements.</li></ul><h3 class="jobSectionHeader">
Hear it from our engineers!</h3>
All nicely said, right? But what if you hear these words from our Data Engineers themselves? Our consultants Sara and Wesley talk about their role as Data Engineer at Xomnia and explain why working at Xomnia is so lively.<h3 class="jobSectionHeader">
Become a Xomnian!</h3>
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 vanity.lekkerkerker@xomnia.com We look forward to meeting you.</div>

Senior Data Platform 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.

Team Overview

We're building a scalable feature platform that powers Ads ML by making high-quality features and training datasets easy to build, share, and maintain. Our small but growing team works on projects like batch &amp; realtime feature management platform, training set generation platform, sequence features platform and, agentic and automated ML workflows for feature lifecycle management.

We are looking for an engineer with experience in building high-scale data infrastructure and exposure to ML platforms to help evolve and scale our feature management systems.

This is not a pure ML modeling role. The ideal candidate is excited about building reliable infrastructure, data pipelines, and developer-facing tools that make ML engineers more productive.

What You'll Do
<ul>
<li>Design and build data infrastructure that supports large-scale feature and training set computation, transformation, and storage.</li>
<li>Develop frameworks for batch and real-time features with a focus on reliability, scalability, and ease of use.</li>
<li>Build platform capabilities for feature governance, including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning</li>
<li>Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems.</li>
<li>Build systems that support agentic ML workflows, including automated feature discovery, feature quality evaluation and feature lifecycle management</li>
<li>Contribute to operational excellence through observability, performance tuning, reliability engineering, and cost optimization initiatives.</li>
</ul>
What You Bring
<ul>
<li>3+ years in data infrastructure/platform engineering or ML infrastructure platforms.</li>
<li>Hands-on experience building production services, data pipelines, APIs, workflow systems, or developer tools.</li>
<li>Experience with at least one distributed data or compute system such as Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery, or similar technologies.</li>
<li>Familiarity with ML data workflows such as feature generation, training dataset creation, batch processing, real-time data processing, model training, experimentation, or online serving.</li>
<li>Strong coding skills and ability to write clean, maintainable, well-tested code.</li>
<li>Experience building intelligent automation or agentic workflows for ML systems is a strong plus</li>
<li>Experience with ML infrastructure and MLOps workflows spanning feature engineering, training pipelines, experimentation, model deployment, and online serving is a plus</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>

Machine Learning Systems Engineer, Ads ML Platform

Curve Royalty Systems

<div>Curve are looking for an experienced Senior Java Engineer to join our growing organisation. This role will be central to the data engineering team whose purpose is to re-architect our backend financial data mapping and transformation processes into ETL pipelines optimised for cost, speed, accuracy and scalability.

This is a key role within a highly collaborative engineering team, working on systems that process complex royalty, financial and rights-related data at significant scale. You will help shape the next generation of Curve's platform, replacing legacy workflows with robust, testable and scalable Java-based services and data pipelines.

The ideal candidate will be comfortable working across software engineering, data engineering and cloud infrastructure. They will bring strong backend engineering experience, a pragmatic approach to technical decision-making, and the ability to work closely with product, engineering and operational teams to deliver reliable systems that support our clients and their artists, labels, distributors and publishers. 


Responsibilities:
<ul>
<li>Collaborate with stakeholders in the product and engineering teams to shape, deliver and maintain a brand-new Best-in-Class royalties platform</li>
<li>Migrate existing business logic from legacy applications to Java modules running in ETL pipelines scaled to run thousands of concurrent processes</li>
<li>Contribute to the architecture, deployment and optimisation of secure and highly performant infrastructure via IaC and CI/CD pipelines</li>
<li>Contribute to the architecture, development, deployment, support, testing and monitoring of software across test, integration and production environments</li>
<li>Debug software and infrastructure components and identify defects for remediation</li>
<li>Design and coding of Apache Beam pipelines to deliver distributed, scalable and highly performant systems using Java</li>
<li>Help define engineering standards, patterns and best practices for backend Java development and ETL pipeline design</li>
<li>Work with large, complex datasets, ensuring transformations are accurate, auditable and performant</li>
<li>Contribute to technical design discussions, architectural reviews and implementation planning</li>
<li>Build systems with observability, resilience, security and operational support in mind</li>
<li>Support the continuous improvement of our development workflows, deployment processes and engineering tooling</li>
<li>Work closely with QA and Technical Operations teams to ensure software is tested, monitored and supportable in production</li>
<li>Take ownership of technical problems from investigation through to delivery and ongoing improvement</li>
<li>Share knowledge with the wider engineering team through documentation, code reviews, mentoring and collaborative problem-solving</li></ul> 


Requirements:
<ul>
<li>6+ Years software engineering experience at a senior level</li>
<li>Excellent written and verbal communications skills</li>
<li>Significant hands-on experience in enterprise level software development</li>
<li>Solid understanding of ETL processes and implementation</li>
<li>Advanced technical skills in the areas of microservices, APIs and Java</li>
<li>Willingness to learn, coach and mentor</li>
<li>Great team collaboration skills</li>
<li>Ability to take responsibility for the product</li>
<li>Strong understanding of software design principles, clean code, testing and maintainability</li>
<li>Experience designing, building and supporting backend systems in production environments</li>
<li>Comfortable working with cloud-based infrastructure, CI/CD pipelines and modern deployment practices</li>
<li>Experience working with non-relational database technologies, data modelling and large-scale data processing</li>
<li>Ability to balance technical quality with pragmatic delivery in a fast-moving environment</li>
<li>Strong debugging, analytical and problem-solving skills</li>
<li>Comfortable working in a distributed or remote-first team environment</li>
<li>A proactive approach to ownership, communication and continuous improvement</li></ul> 


Experience in the following would be an advantage: 
<ul>
<li>Music Industry / Royalties / Financial Services</li>
<li>Dataflow (Apache Beam), Spark, or similar technologies</li>
<li>JavaScript / Typescript</li>
<li>Google Cloud Platform, AWS or similar cloud platforms</li>
<li>Building systems that require strong auditability, traceability and data accuracy</li>
<li>Working with financial calculations, reporting platforms or revenue allocation systems</li></ul> 
 
About You 

You are a thoughtful and experienced engineer who enjoys solving complex backend and data-processing problems. You care about quality, but you are pragmatic enough to know when to move quickly and when to slow down and get the foundations right.

You are comfortable taking ownership of important technical work, but you also value collaboration and shared understanding. You enjoy working with other engineers, product managers, QA specialists and operational teams to make sure what gets built is useful, reliable and maintainable.

You do not need prior music industry experience, but you should be interested in working on technology that supports independent labels, distributors, publishers and rights-holders. You will be joining a team that values trust, communication, technical curiosity and continuous improvement. 


Why join Curve?

At Curve, you will have the opportunity to work on meaningful, technically challenging systems at the heart of the independent music industry. Our platform supports complex royalty processing, financial data transformation and reporting workflows for a growing global client base.

You will join a growing technology team with a strong focus on engineering quality, collaboration and scalable delivery. This role offers the chance to influence architecture, improve core platform capabilities, and contribute directly to systems that make a real difference for our clients and the creators they represent.</div>

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