Location: UK or Portugal

Department: Engineering

Employment Type: Permanent

About YLD:

Our goal is to help our clients keep moving forward. We work with them to build the skills and capabilities they need to stay ahead of the competition, and we know our success only happens when they succeed. We’re a team of curious, talented people, and we’re committed to making YLD a place where great people want to work, grow, and stay. We’re a remote-first consultancy specialising in software engineering, product design, and data. Our teams are based across London, Lisbon, and Porto, and we create digital solutions that continue to deliver value long after our work is done.

About the role:

As a Senior Data Engineer, you’ll be part of a client team building innovative products. We expect you to be curious, passionate, driven, and enthusiastic. You’ll be proficient at problem-solving, and crafting scalable, resilient, and fault-tolerant architectures. You’ll be an effective communicator and a team player. You and your team will move in a fast-paced engineering environment, achieving outstanding results and delivering exciting projects.

About you:

A YLD Senior Data Engineer is a highly skilled engineer who spans across data engineering and analytics engineering, and knows where the boundaries sit. You've built pipelines and transformation layers. You've inherited messy data projects and made them good. You have opinions about how data teams should work and the humility to adapt them to context.

You have a real passion for the craft and are an active learner who gets excited by the variety that consultancy brings: different clients, different stacks, different problems.

Your day-to-day responsibilities will look like this:

• Delivering data work on client engagements: pipelines, transformation layers, models, and the infrastructure around them
• Adapting to different client contexts, legacy warehouse migrations, greenfield lakehouses, struggling transformation layers that need rescuing
• Defining and evolving our internal standards for data work: testing, documentation, project structure, code review
• Mentoring and growing data engineers across the company
• Showing up for client team moments (internal speakers, learning sessions, social events) to build strong working relationships.
• Contributing to proposals and helping shape engagements during the sales process
• Representing YLD externally through writing, speaking, and contributing to the wider data community.

You’ll have the following skills and experience:

• SQL as engineering: You write SQL that's reviewable, testable, and performs at scale. You understand query planning, engine quirks, and how materialisation choices affect cost and performance
• Python for data: You write typed, testable Python for pipelines and tooling. You've built and maintained production data systems, not just notebooks
• Data modelling: You've made deliberate choices between dimensional, Data Vault, normalised, and denormalised designs. You can explain those trade-offs in terms of flexibility, query performance, and maintainability
• Transformation architecture: You design transformations that are idempotent, incremental, and dependency-aware. You think in DAGs, not scripts
• Pipeline design: You understand batch, streaming, and micro-batch trade-offs. You consider latency, complexity, cost, and reprocessability. And choose the right approach for the problem
• Data testing: You write tests as code, schema contracts, assertions, and transformation logic. You know what to catch at build time vs. defer to observability
• Data observability: You treat data reliability like site reliability. Measurable indicators, alerting, incident response, and root cause analysis
• CI/CD for data: You version, test, and deploy pipelines like software. Environment promotion, rollback strategies, and infrastructure as code for reproducible environments
• Data governance: You've implemented lineage, cataloguing, sensitive data classification, or access control. Not just built pipelines, but made them auditable and secure
• Cost-conscious: You've optimised warehouse spend, storage strategies, or job efficiency. You treat compute as a resource to manage, not ignore
• Platform fluency: You've worked across the modern stack. Orchestration (Airflow, Dagster), warehouses (Snowflake, BigQuery, Databricks), ingestion (Fivetran, Airbyte, custom), and transformation (dbt, Spark)
• Cross-functional fluency: You translate engineering constraints into business terms and negotiate realistic commitments

You’ll be:

• Self-motivated and proactive
• Comfortable with ambiguity, experimentation, and iteration
• Collaborative by default. You work well in teams and across teams
• Analytical and detail-oriented in your approach to problems
• Comfortable context-switching across clients, stacks, and problem types
• Willing to shape engagements, not just deliver them: contributing to proposals, scoping, and client relationships
• Active in the wider data community: writing, speaking, or open-source contribution
• Genuinely committed to diversity, equity, and inclusion

Benefits you'll get:

• Company Private Health care
• Enhanced fully paid maternity and paternity leave for up to 6 months
• Company’s Pension Scheme (UK Only)
• 25 days annual holiday (excluding Public Holidays)
• £2000/€2000 annual allowance for Training/Conferences
• £300/€300 annual allowance for additional hardware
• Wellbeing & Performance Support via Oli including Therapy and Coaching
• Discretionary Bonus (depending on Company performance and results)
• Company laptop
• Generous referral schemes

Our typical Recruitment Process looks like this:

• 1st Interview with someone from the Talent team (30-45 Minutes)
• Technical Interview with our Senior Developers (90 Minutes)
• Call with the Head of Engineering (60 Minutes)

Get a glimpse of what it's like working at YLD! 🤳

Check out our LinkedIn page

We live and breathe our values, and know you will too:

• Growing every day
• Including everyone
• Relationships built on honesty and ethics
• Inspiring solutions
• Winning together

We’re an equal-opportunity employer and value diversity in all its forms. We do not discriminate based on race, religion, colour, national origin, gender, sexual orientation, pregnancy or maternity, age, marital status, or disability. We also offer a remote-first working environment, with flexible working and work–life balance as standard for all employees.

About Us

Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world’s biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified’s AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Acer, Gucci, Lorna Jane, GoPro, and many more.

We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day. 

About the Role

We’re looking for a talented multi disciplinary Senior Data Platform Engineer with passion for infrastructure, who will be responsible for the performance, scale, and stability of our core data platform products. We are a data-driven organization, ingesting data at high rates, with demands increasing each day.

As a Senior Data Platform Engineer, you will be part of the Data Platform group and will be responsible for a large scale production data platform that serves as the core infrastructure of our products. You'll develop self-service tools that support the accessibility of our platform for the use of our users from R&D and Analytics departments. We will look to you to be a center of knowledge, consult, and share your expertise with others.

What You'll Be Doing

• Lead the development of AI-ready data platform foundations, including data quality, contracts, observability, and self-service tooling that power machine learning and AI-driven products.
• Administrate, provision and monitor our different platform products.
• Develop, maintain and enhance the Applicational infrastructure that is working tightly with our Data Platform infrastructure tools.
• Guide development teams and mentor other team members.
• Use your creativity to resolve complex and high scale data related issues
• Research new technologies, starting from POC level to production grade systems.

Qualifications

• 6+ years prior experience as a Data Platform Engineer / Big Data Infrastructure engineer or equivalent.
• Deep understanding of distributed systems, in terms of ingestion, storage and access.
• Hands-on experience with Data Streaming technologies: Apache Kafka / Apache Pulsar / Spark Streaming / Kstream / Apache Flink 
• B.Sc. in Computer Science (or equivalent)
• Experience working on high scale, production-grade projects

Advantage

• Experience with tools like Apache Spark and Databricks.
• Experience with the Cloud Native stack( Kubernetes / Prometheus/Istio etc.)
• Experience with a cloud provider (AWS, Google etc.)
• Experience with Infrastructure tools (Helm, Ansible, Terraform etc.) 
• Experience with Scala

Life at Riskified

We are a fast-growing and dynamic tech company with 750+ team members globally. We value collaboration and innovative thinking.

We’re looking for bright, driven, and passionate people to grow with us.

Some of our Lisbon Benefits & Perks:

• Hybrid mode of work
• Flexible schedule
• Recharge weekends
• Healthcare & dental benefits
• Fully-stocked kitchens
• Commuter benefits
• Benefits package per month—per your choice, e.g., work-from-home equipment, gym membership, wellbeing activities, and more.
• Wellness program
• Celebrations and activities
• Team events
• Happy hours
• Awesome Riskified gifts and swags
• Volunteer programs
• Personal development
• Global onboarding
• Role-based technical skills training
• Full access to Udemy

In the News

C-Tech: We need to find the balance between leveraging innovative AI solutions and using them cautiously

Built In: How We Built This: A Riskified Technologist Unpacks The Company’s Beacon Technology

Globes: Riskified is among Israel’s fastest growing companies  

Yahoo: Riskified Earns "Top Rated" Award Across Four TrustRadius Solution Categories

Riskified is deeply committed to the principle of equal opportunity for all individuals. We do not discriminate based on race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, or any other status protected by law.

Let's start with the role

As a Product Analyst on the Sportsbook Product team, you will help shape how product performance is measured by defining the right questions to ask, and scaling analytics methods and tools to support our growing business. You will drive high-quality, high-velocity decisions for Sportsbook’s diverse product teams while directly reporting to our Head of Sportsbook Product.

We’re looking for an experienced product analyst to be responsible for defining and tracking KPIs, supporting strategic initiatives, evaluating A/B tests through 3rd-party experimentation platforms, and aggregating data from multiple sources—from GA4 to our big data lake of transactional data—to help the team achieve a 360° view of our customers.

Our ideal candidate is a great storyteller, using data to support product roadmaps and ensure that any new feature launched is continually improved through data insights and impactful narratives. Your input will be crucial in decision-making across all major product strategies and initiatives for new feature development and ongoing product improvements. 

• Work alongside the Sportsbook Product Team to support our dynamic and fast-paced Product roadmap, providing insights to help achieve our Product vision by defining, monitoring and reporting on KPIs and product metrics.
• Leverage the transactional data lake to connect customer journeys with business outcomes.
• Support our experimentation process by analyzing A/B test results and helping expand our internal experimentation framework.
• Implement GA4 tagging to map all user journeys, identify and highlight customer pain points across products, and work closely with the Sportsbook product management team to prioritize these in the roadmap.
• Synthesize data from a variety of sources, in close collaboration with BI and other stakeholders, to develop dashboards, reports, and visualizations (e.g., funnels in Looker Studio or other internal tools) that drive understanding and inform action across the Sportsbook vertical.
• Ensure data quality, consistency, and governance across all analytics initiatives to maintain trust and reliability in insights.
• Use data analytics, data visualization, and data modeling techniques to extract actionable insights that will facilitate prioritization and product strategy formulation.
• Advise and inform the Sportsbook team at each stage of the product lifecycle—from supporting product and design teams during discovery to measuring the impact of features post-launch—while collaborating closely with Product Managers, Engineers, Designers, BI Analysts, and Product Analysts from other divisions.

What  you’ll bring:

A great candidate for this role is passionate about working in a fast-paced product environment and is eager to enhance our product offering while creating an exceptional betting experience. 

• 2+ years of product analytics experience in a consumer internet business, or within a high-velocity, high-growth product or business unit.
• Experience assessing the impact of A/B experiments in a fast-paced product development cycle, ideally using platforms such as Kameleoon or Optimizely.
• Proficiency in SQL for data manipulation.
• Ability to independently determine and establish data analysis priorities, balancing ongoing projects with requests from various stakeholders.
• Experience with GA4 and other product or experience analytics platforms, with strong skills in creating dashboards in Looker Studio or similar visualization tools.
• Strong written communication skills to share insights and influence stakeholders.
• Detail-oriented, impact-driven, customer-centric approach to data analysis.

Nice to have:

• Previous experience in the sports betting industry.
• Experience with BI/visualization tools such as PowerBI.
• Familiarity with Databricks or similar big data platforms.

Kaizen Gaming Perks

• 🕑 Hybrid way of working;
• 🏃 A buddy will support you with your onboarding;
• 💸 Competitive pay & bonus scheme;
• ⭐Developmental 360° feedback framework;
• 💰 Monthly meal allowance;
• 👩‍⚕️ Private health insurance for you and your family;
• 📚 Unlimited access to Udemy & continuous training;
• 👨‍👩‍👧‍👦 Family Support.
• #LI-Hybrid
• #LI-GP2

Let's start with the role

As the team lead of an AI product team you will lead and guide the team's efforts in delivering high impact AI products. You will be at the core of AI developments, analyzing data, building machine learning models, collaborating with the tech team to create successful AI products. 

The ideal candidate will combine a deep understanding of machine learning algorithms and proven extensive experience in building  ML/AI powered applications in production along with previous experience of leading and managing AI teams.

As a Data Science Team Lead, you will:

• Manage a team of 5 to 7 skilled data scientists and machine learning engineers. 
• Translate product requirements to machine learning problems and identifying areas where AI can have the most business impact;
• Analyze data to identify significant patterns and generate insights;
• Perform exploratory data analysis (EDA) and feature engineering to support the modeling process;
• Implement best practices on model selection, parameter tuning and optimization.
• Run comparative experiments for model training;
• Analyze ML metrics to evaluate different potential solutions;
• Manage the full lifecycle of AI features, from data collection to model design and to implementation and optimization in production environments;
• Mentor and share knowledge with more junior members and guide the team through complex projects. 

What you’ll bring

• Previous experience as a people manager;
• Expert knowledge of machine learning algorithm and their theoretical foundations;
• Extensive hands-on experience in delivering machine learning models to production;
• Experience in developing MLOps solutions;
• Knowledge of Deep learning;
• Proficiency in Python’s machine learning ecosystem and solid software engineering skills (OOP);
• Strong skills in teamwork, communication, and analytical thinking;
• Fluency in English, both oral and written.

• Experience with Big Data tools  (Spark/PySpark) and cloud environment, ideally Azure / Databricks;
• Previous experience in pricing optimisation;
• Previous experience in forecasting;
• Previous experience in the betting industry.

Kaizen Gaming Perks

• 🕑 Hybrid way of working
• 🏃 A buddy will support you with your onboarding
• 💸 Competitive pay & bonus scheme
• ⭐Developmental 360° feedback framework
• 💰 Monthly meal allowance
• 👩‍⚕️ Private health insurance for you and your family
• 📚 Unlimited access to Udemy & continuous training
• 👨‍👩‍👧‍👦 Family Support
• #LI-HYBRID
• #LI-AP

Let's start with the role

At Kaizen, we aim to leverage the capabilities offered by modern AI algorithms to continuously improve our product and business. Kaizen’s AI department consists of product, platform and research teams and lies at the core of that mission. We develop AI products for various applications, ranging from detection of fraudulent activity to personalized gaming recommendations, and from AI-powered co-pilots to CRM optimizations. 

We build our teams to be self-driven, autonomous and cross-functional. Within these teams, you will have the opportunity to work with Data Scientists, Machine Learning Engineers, Data Engineers, Data Analysts, Product Owners and Agile Delivery Leads.

As a Machine Learning Software Engineer, you will focus on delivering robust and scalable Machine Learning pipelines and you will support the operationalization of Machine Learning models. 

• Design, develop and maintain scalable model training and inference pipelines in a distributed production environment;
• Design, develop and maintain microservices in Python that host and serve ML models on production;
• Design, develop and maintain internal tools that enable CI/CD/CT, performant feature engineering, experiment tracking, data and model versioning.

What you’ll bring

• Ηands-on experience in software development using Python on a production environment;
• Good understanding of:
• Software system design; 
• The ML project lifecycle;
• MLOps concepts and tools such as MLflow or Kubeflow;
• ML algorithms and models.
• Experience with cloud providers like Microsoft Azure or AWS;
• Experience with PySpark and Databricks.

Kaizen Gaming Perks

• 🕑 Hybrid model of working
• 🏃 A buddy will support you with your onboarding
• 💸 Competitive salary package and bonus scheme
• 👩‍⚕️ Health and life insurance for you and your family
• 💰 Monthly meal allowance 
• ⭐ Developmental 360° feedback framework
• 📚 Unlimited access to Udemy & continuous training
• 🚗 Commuting allowance
• 👨‍👩‍👧‍👦 Family Support
• #LI-Remote

Let's start with the role

At Kaizen, our aim is to make data driven decisions in order to automate our servicers while also focusing on offering tailored customer experiences. Our machine learning team is dedicated towards this mission by building a variety of models, from binary classification tasks up to recommendation systems. We focus on transforming business needs into production applications and we cover a wide range of business sectors utilizing different data types and handling a broad project diversity. 

Our teams comprise of three different roles, data scientists, machine learning engineer and data engineers so that they include the full skillset to deliver projects to production.

We are currently looking for data scientists in all levels to join our teams. The role should combine strong knowledge of machine learning algorithms, analytical skills, experimental design etc. to support the model development process.

• Translate business requirements to machine learning problems;
• Perform EDA and feature engineering;
• Run comparative experiments for model training;
• Implement best practices on model selection, parameter tuning etc.

What you’ll bring

• A background in Computer Science, Statistics, Math or related field;
• Strong knowledge of machine learning algorithm and respective theory;
• 2-8 years of hands-on experience in delivering machine learning models to production;
• Knowledge of the Python machine learning ecosystem;
• Experience with Spark (PySpark);
• Solid software background in OOP;
• Strong skills in teamwork, communication, and analytical thinking;
• Fluency in English, both oral and written.

Nice to have

• Experience with Azure / Databricks;
• Knowledge of Deep learning;
• Experience in recommendation systems.

#Artificial Intelligence (AI) #Machine Learning (ML) #Data Science (DS)

Kaizen Gaming Perks

• 🕑 Hybrid way of working
• 🏃 A buddy will support you with your onboarding
• 💸 Competitive pay & bonus scheme
• ⭐Developmental 360° feedback framework
• 💰 Monthly meal allowance
• 👩‍⚕️ Private health insurance for you and your family
• 📚 Unlimited access to Udemy & continuous training
• 👨‍👩‍👧‍👦 Family Support.
• #LI-Remote
• #LI-PROMOTE

Let's start with the role

As a GenAI Senior Data Scientist, you will be at the forefront of our AI developments,  analyzing data, building Gen AI powered applications and/or agentic architectures. You will be responsible for selecting the right LLMs, performing prompt engineering and model fine-tuning to support our AI products. You will collaborate closely with cross-functional tech teams to deliver impactful, production-grade AI solutions. The ideal candidate has a deep understanding of LLMs and agentic architectures, along with proven experience building and deploying such applications in production environments.

As a GenAI Senior Data Scientist you will:

• Translate product requirements to AI problems and identify areas where AI can drive the most business impact;
• Analyze data to uncover significant patterns and generate actionable insights;
• Architect agentic and GenAI systems;
• Select appropriate models for the right tasks and tune their performance;
• Perform exploratory data analysis (EDA and feature engineering to support the modeling process;
• Apply best practices on model selection, parameter tuning etc.;
• Run comparative experiments for model training;
• Analyze ML metrics to evaluate different potential solutions;
• Manage the full lifecycle of AI features, from data collection to model design and to implementation and optimization in production;
• Mentor and guide junior members, sharing knowledge and leading complex projects. 

What you’ll bring:

Must have:

• Hands on experience with GenAI and Agentic applications;
• Extensive hands-on experience in delivering AI driven products to production;
• Experience in scaling and optimisation of AI applications;
• Knowledge of machine learning algorithm and respective theory;
• Knowledge of the Python machine learning ecosystem and solid software background in OOP;
• Strong skills in teamwork, communication, and analytical thinking;
• Fluency in English, both oral and written.

Nice to have:

• Experience with Big Data tools  (Spark/PySpark) and cloud environment, ideally Azure / Databricks;
• Previous experience in LLM fineturing;
• Previous experience with LLM serving;
• Knowledge of Deep learning. 

Kaizen Gaming Perks

• 🕑 Hybrid way of working
• 🏃 A buddy will support you with your onboarding
• 💸 Competitive pay & bonus scheme
• ⭐Developmental 360° feedback framework
• 💰 Monthly meal allowance
• 👩‍⚕️ Private health insurance for you and your family
• 📚 Unlimited access to Udemy & continuous training
• 👨‍👩‍👧‍👦 Family Support.
• #LI-Hybrid
• #LI-ap1

ComplyAdvantage Technology

At Comply, we are building cutting-edge solutions that help prevent money flowing to and from bad actors to create a safer world. Your work will allow our customers to find out who is associated with crimes, financial and political risks, what that association is, and when it occurred, and it will dynamically update their state as new information emerges across a huge range of sources.

What you will be doing

As a Machine Learning Engineer, you will: 

• Build/train and productionize machine learning models for your squad
• Build capabilities to monitor model performance and feature drift
• Where appropriate re-use public models and techniques such as prompt engineering and RAG to reduce time to value
• Collaborate with other software engineers in a cross functional team to design and implement intelligent services
• Design software with scale, transparency and ease of operation in mind, writing maintainable, performant and well-tested code in Python
• Integrate ML models into new and existing data pipelines to drive positive impacts for CA’s customers, including feature engineering as well as building APIs and consuming and producing event streams as inputs and outputs of models

Our Tech Stack:

• Our technology stack is designed to run on public cloud architectures, notably AWS and GCP
• We use Python and Kotlin in the backend and TypeScript, ES6 and React in the frontend
• We make substantial use of  modern database technologies (eg. Yugabyte) as well as Spark and cloud based object stores for big data processing
• We also use an event-sourced model powered by Kafka for our communication bus and gRPC for our intra-service communication protocol
• Our data and AI teams use a wide range of machine learning libraries, large scale hybrid columnar data stores such as Databricks, Spark for stream and big data processing in combination with Kafka, as well as some graph databases
• We use modern observability solutions (Grafana) and deploy our code using ArgoCD

We have a strong emphasis on engineering excellence and strive to ship the best possible code and the best possible solutions to our customers.

About you:

• Experience maintaining and scaling machine learning-powered applications in production environments.
• Experience building scalable backend applications (preferably with Python).
• A track record of working in multi-disciplinary teams alongside Data Scientists, ML Engineers, and Product Managers.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) or with containerized infrastructure (e.g., Kubernetes, Docker, ArgoCD, Argo Workflows).
• Strong communication skills and a collaborative mindset, with the ability to contribute to system design discussions and mentor more junior engineers.

Nice to have:

• Experience working with PySpark or other distributed data processing frameworks.
• Background in building data-intensive applications or distributed systems using map-reduce style architectures.
• Familiarity with event-driven or microservice architectures.

What’s in it for you? 

• Equity as we want you to have a part of what we are building 
• Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
• Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best 
• We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
• You will also get a new starter budget to kit out your home office 
• Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve 
• Annual learning budget (prorated based on start date) to drive your performance and career development

What you will be doing:

We are building cutting edge solutions that help reveal the truth for a safer world and we are looking for Machine Learning Engineers to help us do this! You will engineer machine learning models, tooling and data pipelines for our linked data ecosystem and work on models to determine whether the people and companies our clients are screening and monitoring are linked to financial crime, and to improve recall while reducing noise in the results. 

As a Junior Machine Learning Engineer, you will:

• Build/train and productionize machine learning models for your squad
• Build capabilities to monitor model performance and feature drift
• Where appropriate re-use public models to reduce time to value
• Collaborate with other software engineers in a cross functional team to design and implement intelligent services
• Be mentored by senior engineers to design solutions with scale, transparency and ease of operation in mind, and to write maintainable, performant and well-tested code in Python
• Work with mid and senior engineers to integrate ML models into new and existing data pipelines to drive positive impact for CA’s customers, including feature engineering as well as building APIs and consuming and producing event streams as inputs and outputs of models

Our Tech Stack:

• Our technology stack is designed to run on public cloud architectures, notably AWS and GCP. 
• Development is organized around Kotlin and Python for our backend languages and TypeScript/ES6+React for our frontend stack. 
• We make substantial use of relational database technologies, notably Postgres, and also use of  a distributed SQL database as Yugabyte
• We also use an event-sourced model powered by Kafka for our communication bus and gRPC for our intra-service communication protocol. 
• For our data and AI teams, experience in machine learning development and very large-scale columnar data stores (e.g. Apache HBase, Databricks) is key, as well as experience with large-scale data streaming technologies such as Apache Spark, graph databases (e.g. Neo4j, AWS Neptune, TigerGraph)
• We use modern observability solutions built on Grafana Cloud, and deploy our code using ArgoCD

We have a strong emphasis on engineering excellence and strive to ship the best possible code and the best possible solutions to our customers.

About you:

As a Junior Machine Learning Engineer, you will have:

• Demonstrable python software development skills
• A degree with some mathematical content and formal machine learning education either subsequent to your degree (e.g. as a masters) or as a core part of your degree
• Demonstrable experience of building ML models using a range of machine learning algorithms and techniques either from previous jobs or personal and academic projects 

Education: 

• BSc/BA degree in computer science, engineering or related discipline OR relevant years of experience in required skills.

What’s in it for you? 

• Equity as we want you to have a part of what we are building 
• Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
• Unlimited Time Off Policy - A work-life balance and focus on our well-being are critical to keeping us performing at our best 
• We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
• You will also get a new starter budget to kit out your home office 
• Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve 
• Annual learning budget (prorated based on start date) to drive your performance and career development 

As a Machine Learning Platform Engineer at Iterable, you will design, evolve, and maintain our core ML infrastructure and the paved roads on which we build intelligence into our product. As a high tech marketing platform, we work with thousands of high scale and diverse enterprise customers. The scale and diversity of these workloads, supporting personalization with deep customizability, presents unique and exciting challenges for platform engineering. 

One of our core values is a growth mindset and Iterable is a company where everyone can grow. If this is a role that excites you, please do apply as we value applicants for the skills they bring beyond a job description.

What You’ll Do

• Lead the end-to-end development of ML pipelines, from prototyping and experimentation through to production deployment, enabling AI-powered features at scale.
• Design, build, and maintain the core infrastructure that powers our ML services (e.g., Databricks, AWS, Ray, Kubernetes).
• Develop robust observability and experimentation frameworks to ensure reliable model deployment, monitoring, and continuous iteration.
• Partner closely with Data Science teams, treating the ML Platform as a product—removing infrastructure bottlenecks and empowering them to deliver high-quality models efficiently and confidently.

What We’re Looking For

• 3+ years of experience in backend and/or infrastructure engineering.
• Strong experience with infrastructure-as-code practices (e.g., Pulumi, Terraform, CloudFormation).
• Experience working with service-oriented architectures and integrating ML services into high-scale backend systems.

Nice to Have

• Hands-on experience building and operating ML pipelines, including traditional recommender systems and modern deep learning training and serving systems.

What we offer 

• Competitive salaries & meaningful equity
• Private Medical Insurance
• Life/Risk Assurance
• Meal Allowance: 8.55€ per day
• Community Days (days for us to give back to the community) 
• Paid Annual Leave (22 days)
• Global Lifestyle Reimbursement Account
• Paid Sabbatical
• Complete laptop workstation

What you will be doing:

We are seeking a highly skilled Senior Site Reliability Engineer (SRE) to join our Data Infrastructure team. You will be responsible for ensuring the reliability, availability, and performance of our critical data systems running on AWS and GCP. Your expertise in cloud infrastructure, automation, and operational excellence will be crucial in supporting our Product trough our global client base.

As a Senior Site Reliability Engineer you will:

• Design, implement, and maintain highly available and reliable data infrastructure services, including SQL, NoSQL, Kafka, and Spark-based data layers. Define and monitor Service Level Objectives (SLOs) and Service Level Agreements (SLAs).
• Participate in an on-call rotation to respond to incidents and ensure rapid resolution of production issues. Conduct thorough post-incident reviews to identify root causes and implement preventative measures.
• Manage and automate cloud infrastructure using Terraform and Helm, adhering to GitOps principles.
• Implement and maintain comprehensive monitoring, logging, and tracing solutions to proactively identify and resolve performance and reliability issues.
• Monitor and manage data infrastructure capacity, plan for future growth, and optimize performance through tuning and automation.
• Develop and maintain automation scripts and tools to streamline operational tasks, improve efficiency, and reduce manual effort.
• Ensure the security and compliance of data infrastructure services, implementing best practices for access control, data protection, and vulnerability management.
• Collaborate with development and data engineering teams to ensure smooth deployments and operational support. Maintain thorough documentation of infrastructure configurations, processes, and procedures.
• Manage and maintain distributed databases running within a Kubernetes environment.

Our Tech Stack:

• Cloud-Based Infrastructure: Fully cloud-based with a Kubernetes-focused tech stack. Compute workloads run in Kubernetes clusters across multiple regions.
• Infrastructure Management: Heavy use of Terraform and Helm, adhering to GitOps paradigms for managing cloud infrastructure and Kubernetes applications.
• Core Technologies: Extensive use of Kafka, distributed PostgreSQL and Cassandra QL, Elasticsearch, and Databricks/Spark. Development of inter-cloud failover options to support multi-cloud plans.
• Wide Array of Applications: Teams build and release containerised applications for low latency APIs, machine learning models, and data processing pipelines.

About You:

• Experience as an SRE managing cloud infrastructure (AWS and/or GCP) and data systems (Apache Kafka, Apache Spark, Elasticsearch, PostgreSQL, Cassandra). Proven track record of improving reliability and availability in complex production environments.
• Extensive experience codifying infrastructure using Terraform and Helm charts.
• Proven experience managing and troubleshooting distributed databases within Kubernetes.
• Deep understanding of monitoring, logging, and tracing tools and techniques.
• Strong incident response and troubleshooting skills.
• Proficiency in scripting and automation tools.
• Understanding of security best practices for cloud infrastructure and data systems.
• Familiarity with CI tooling, test pipelines, and asset generation (e.g., Docker images, Helm charts). Understanding of security considerations in data systems.

Education:

• BSc/BA degree in computer science, engineering, or related discipline OR equivalent experience in required skills.

Nice to have

• Familiarity with distributed SQL and NoSQL databases such as Yugabyte, Cockroach, Spanner, HBase, or CouchDB.
• Familiarity with data modelling, sharding, and indexing strategies for large-scale databases.

What’s in it for you? 

• Equity as we want you to have a part of what we are building 
• Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
• Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best 
• We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
• You will also get a new starter budget to kit out your home office 
• Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve 
• Annual learning budget (prorated based on start date) to drive your performance and career development 

Our Data & Engineering team is growing, and we’re now looking for a Senior Data Consultant (m/f/*) to join our team in Portugal, supporting our global growth.

As a Senior Data Consultant, you will combine deep hands-on experience in modern data platforms — particularly Databricks — with a strategic, client-oriented mindset. You’ll advise organizations on how to design, implement, and scale data-driven architectures, while guiding them through every stage of their digital transformation journey.

WHAT WE OFFER

• Flexible work options, including fully remote or hybrid arrangements (candidates must be located in Portugal)
• The chance to accelerate your career and work with outstanding colleagues in a collaborative, global learning community across three continents
• Opportunities to shape cutting-edge data projects and see your ideas implemented in real-world solutions
• Balance your work and personal life: choose to work from home, in the office, or in a hybrid setup
• Annual performance reviews and continuous feedback focused on collaboration and growth, not hierarchy
• A personalized development plan and professional advancement opportunities
• Access to learning resources — paid certifications, unlimited Udemy Business, and more
• Local, virtual, and global team events to connect with colleagues worldwide

WHAT YOU’LL DO

• Advise clients on the design and implementation of scalable data architectures using Databricks Lakehouse Platform, with a strong focus on Apache Spark, Delta Lake, and Unity Catalog
• Translate complex business requirements into data strategies, architecture blueprints, and technical roadmaps
• Design, implement, and optimize data pipelines for analytics, machine learning, and business intelligence workloads
• Collaborate with stakeholders — from executives to technical teams — to align data initiatives with business goals
• Ensure data quality, governance, and security best practices within Databricks and related ecosystems
• Support pre-sales and discovery activities by identifying client needs and defining technical approaches
• Mentor junior consultants and contribute to the growth of our Databricks and data consulting expertise
• Stay current with emerging technologies and trends in cloud data platforms and AI-driven analytics

WHAT YOU’LL BRING

• Proven experience in data consulting or architecture, with hands-on expertise in Databricks on Azure, AWS, or GCP
• Deep knowledge of Spark (PySpark/Scala), Delta Lake, and MLflow
• Strong programming skills in Python or Scala, and experience with CI/CD pipelines (GitHub Actions, Azure DevOps, etc.)
• Solid understanding of data modeling, distributed computing, and performance optimization in cloud environments
• Experience advising or working directly with enterprise clients on data modernization or cloud migration projects
• Familiarity with orchestration tools (e.g., Databricks Workflows, Airflow) and infrastructure-as-code (e.g., Terraform)
• Excellent communication and stakeholder management skills, with the ability to translate technical solutions into business value
• Professional proficiency in English (C1 level, written and spoken)

Did we pique your interest, or do you have any questions?
We’d love to hear from you — contact us at recruiting@ultratendency.com

Our Engineering community is growing, and we’re now looking for a Senior Data Engineer - Databricks (m/f/*) to join our team in Portugal, supporting our global growth.

WHAT YOU’LL DO