Feedzai Research focuses on anticipating and solving Feedzai’s long-term goals. We strive to develop ethical cutting edge technology to stay one step ahead of the fraudsters of tomorrow. We work closely with Product and Data Science to build distributed systems that support high-load, operate 24/7 with low latencies, and use Machine Learning to make decisions and fight fraud more efficiently. As a research team, we focus on long-term, disruptive, state-of-the-art research, produce and protect our IP, publish peer reviewed work, contribute to open-source, and partner with external researchers and universities.

We are looking for someone that combines technical knowledge and research skills, is passionate about building cloud native applications that scale to process millions of events per second, while providing low-latency and fault-tolerance guarantees.

Come and change the world with us.

Your Day to Day:

• Design and implement real-time Machine Learning inference systems able to process millions of events per second while achieving low-latency and fault tolerance guarantees.
• Define technical standards and best practices for new cloud-native services, with particular focus on Data and ML Infrastructure.
• Drive architectural decisions for Machine Learning systems workloads, balancing performance, cost, reliability, and user experience.
• Be hands-on, executing the full software development life cycle and writing well-designed and testable code.
• Design and develop Communicate findings and results to internal and external stakeholders, including writing scientific papers and patents.
• Review and evaluate state-of-the-art research work on topics including Data Processing, Machine Learning Systems, Graphs, etc.
• Own services throughout their lifecycle following DevOps principles (“you build it, you run it”).
• Leverage GenAI-assisted development tools to prototype, implement, and iterate on platform capabilities quickly, while maintaining strong engineering and security standards.

You Have & You Know-how: 

• BSc/MSc degree in Computer Science, or a similar technical degree 
• 4+ years of experience in developing high-performance backend services
• Good understanding of distributed systems, multi-threading and OO design principles
• Strong programming skills, preferable in Java (or any JVM language) and Python
• Ability and interest to digest and implement state-of-art research.
• Ability to communicate your findings in a clear way, transforming innovation research into product requirements.
• Ability to work autonomously and take ownership of ambiguous, high-impact technical problems.
• Experience with continuous delivery, monitoring, and operational ownership of services.

Preferred/Valued Qualifications and Skills: 

• Experience with Kubernetes and cloud-native architectures (AWS preferred).
• Familiarity with Big Data technologies such as Spark, Kafka, Cassandra, EMR/Dataflow.
• Knowledge of Machine Learning basics.
• Experience building AI-powered products or platforms used by external customers.

#LI-BR1 #LI-Remote

Project Description

We are looking for an experienced Data Engineer with deep expertise in Databricks to join our advanced analytics and data engineering team. The ideal candidate will play a key role in designing, building, and optimizing large-scale data solutions on the Databricks platform, supporting business intelligence, advanced analytics, and machine learning initiatives. You will collaborate with cross-functional teams to deliver robust, scalable, and high-performance data pipelines and architectures.

Technologies

• Databricks (including Spark, Delta Lake, MLflow)
• Python/Scala
• SQL
• ETL concepts
• Distributed data processing
• Data warehousing
• Cloud Platforms & Storage

What You'll Do

• Lead the design, development, and deployment of scalable data pipelines and ETL processes using Databricks (Spark, Delta Lake, MLflow);
• Architect and implement data lakehouse solutions, ensuring data quality, governance, and security;
• Optimize data workflows for performance and cost efficiency on Databricks and cloud platforms (Azure, AWS, or GCP);
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights;
• Mentor and guide junior engineers, promoting best practices in data engineering and Databricks usage;
• Develop and maintain documentation, data models, and technical standards;
• Monitor, troubleshoot, and resolve issues in production data pipelines and environments;
• Stay current with emerging trends and technologies in data engineering and Databricks ecosystem;

Job Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field;
• 5+ years of experience in data engineering, with at least 2 years of hands-on experience with Databricks (including Spark, Delta Lake, and MLflow);
• Strong proficiency in Python and/or Scala for data processing;
• Deep understanding of distributed data processing, data warehousing, and ETL concepts;
• Experience with cloud data platforms (Azure Data Lake, AWS S3, or Google Cloud Storage);
• Solid knowledge of SQL and experience with large-scale relational and NoSQL databases;
• Familiarity with CI/CD, DevOps, and infrastructure-as-code practices for data engineering;
• Experience with data governance, security, and compliance in cloud environments;
• Excellent problem-solving, communication, and leadership skills;
• English: Upper Intermediate level or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Sep 25, 2025 12:50

The Engineering (Tech) Team is responsible for all Feedzai product development. Together with Product Management and Data Science, we build the next generation of tools to catch fraud in real-time with a machine learning first approach. Formed by engineers and managed by engineers, at Feedzai, you will find one of the most talented teams out there, from junior to senior engineers.

We are fast-paced and provide a safe, open, and collaborative environment that encourages us to lean in, try new things and discover our potential with continuous learning for everyone.

While building the best value for our customers, you will work with a wide range of technical challenges. Such as building distributed systems that need to operate 24/7 and ultra-low latencies, solving UI/UX problems to help fraud analysts to fight fraud more efficiently. In addition, designing extensive databases from relational, NoSQL and graphs, validate and develop new data science techniques and algorithms.

You:

Our philosophy across Engineering includes the following key ideas, which you will have a key role promoting in your team: 

• Teams operate with a “you build it, you run it” DevOps mindset, taking end-to-end ownership of development, deployment, and operations. You'll drive a culture focused on automation, observability, and operational excellence, enabling continuous delivery with confidence.
• Architecture evolves towards a decoupled, microservice-based architecture, positioning it to scale efficiently in a multi-tenant, cloud-native environment. This effort is central to Feedzai’s long-term vision and product evolution

You are a passionate professional with the talent to push engineering excellence, challenge the status quo, and make things happen.

You will excel if you are curious, have a critical mindset, and can drive scalable technical solutions that mesh with our business goals.

Your Day to Day:

• Be hands-on, executing the full software development life cycle
• Write reusable and testable code using the best tools for the job and participate in code reviews
• Contribute to best practices and guidelines for software development
• Contribute to the cloud-native SaaS strategy of Feedzai
• Engage in recruiting activities that allow Feedzai to draw top talent
• Providing support and improvements to our production clients
• Work iteratively within our agile teams to develop our products and underlying technical frameworks
• Participate in an on-call rotation for our mission-critical platform, taking end-to-end ownership to ensure 24/7 reliability, with dedicated compensation.

You Have & You Know-how:

• 3+ years of experience building Java backend software or similar
• BSc/MSc degree in Computer Science, or a similar technical degree (required)
• Strong coding skills and Computer Science fundamentals
• Experience in programming high-performance, concurrent server-side code
• Experience designing and building modern web applications
• Experience with modern distributed systems platforms and patterns such as Spark, RabbitMQ, Kafka or Cassandra
• Contributions to OSS projects 
• Passionate desire to learn and grow
• Able to bring ideas into the team and to work out solutions to tough problems autonomously

The Product Team builds our product to disrupt the financial crime industry from a data-led approach. We partner with our clients using a holistic lens and have result-driven solutions to manage financial risk with a cloud-first platform and a world-class UX interface. Being part of this team, you have a voice in planning, strategizing, and challenging the status quo. Your thoughts and ideas are valued. Our fast-paced and open environment encourages us to lean in, try new things, and  discover our potential. We define and act on what could be in tomorrow's world, not on what is today. Join Us!

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.

Let's start with the role

At Kaizen, we strive to harness the power of 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 structure 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 Senior Machine Learning Engineer, you will focus on delivering robust and scalable Machine Learning pipelines and you will support the operationalization of Machine Learning models. Here's what's up for you:

• Collaborate closely with data scientists in order to deliver production-ready model training pipelines;
• Design scalable solutions in a distributed environment;
• Design scalable inference pipelines and architectures;
• Implement model diagnostics such as evaluation, monitoring flows etc.;
• Automate model deployment, enable REST API model endpoints;
• Develop scalable model serving flows;
• Work on cluster optimization and scalability;
• Develop and maintain internal tools and libraries;
• Write CI/CD/CT pipelines.

What you’ll bring:

• Extensive experience in software development using Python in large scale, high-performance production environment;
• Significant hands-on experience in designing ML software systems;
• Significant experience with cloud environments like Microsoft Azure or AWS;
• Hands-on experience with Spark and PySpark;
• Excellent problem solving and communication skills
• Good understanding of:

• • Software system design; 
  • The ML project lifecycle;
  • MLOps concepts and tools such as MLflow or Kubeflow;
  • ML algorithms and models.

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

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

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 Senior Data Scientist, you will be at the forefront of our AI developments,  analyzing data, building machine learning models to support our AI products and working along with the rest of the tech team to create successful AI products. The ideal candidate will have a deep understanding of machine learning algorithms and proven extensive experience in building  ML/AI powered applications in production.

As a Senior Data Scientist you will:

• 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 actionable insights;
• 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 environments;
• Mentor and guide junior members, sharing knowledge and leading complex projects. 

What you’ll bring:

Must have:

• Expert knowledge of machine learning algorithm and respective theory;
• Extensive hands-on experience in delivering machine learning models to production;
• Experience in developing MLOps solutions;
• Knowledge of the Python machine learning ecosystem and solid software background in OOP;
• Knowledge of Deep learning;
• 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;
• Experience in recommendation systems;
• Experience in GenAI application development;
• Relevant industry experience i.e. Fraud detection, CRM, Sportsbook etc.

Kaizen Gaming Perks

• 🕑 Hybrid way of working & remote options
• 🏃 A buddy will support you with your onboarding
• 💸 Competitive pay and bonus scheme
• 👩‍⚕️ Private health insurance for you and your family
• 💰 Monthly meal allowance 
• ⭐Developmental 360° feedback framework
• 📚 Unlimited access to Udemy & continuous training

#LI-Remote

Let's start with the role

As a Principal Data Scientist, you will play a critical role in leveraging data and AI to deliver value and create a competitive advantage for the organization. The ideal candidate will be a tenured Data Scientist, ML or AI engineer that has a proven track record of designing and implementing cutting-edge, data-intensive and AI-empowered applications along with the corresponding ML/DL algorithms.

As a Principal Data Scientist your main responsibilities will be

• Architecture: Architect scalable, reliable and high-performance AI applications along with their corresponding ML/DL algorithms.
• Innovation: Tech-lead the AI tribe in order to deliver state-of-the-art AI models in production.
• Mentorship: Inspire and mentor fellow data scientists, fostering technical and soft skill growth.
• Pioneering: Stay ahead of the AI curve, applying emerging technologies to enhance our capabilities and disrupt the industry. 
• Strategic Planning & Prioritization: Define the company-wide AI technical and product roadmap, in-line with the business product roadmap. Resist the AI hype and enable impact-driven prioritization with quick and impactful PoCs that demonstrate the value.
• Autonomy & end-to-end Ownership: From ideation all the way to operationalization and maintenance, demonstrate autonomy on high-complexity projects and ownership of the outcome.

What you’ll bring

• 8+ years of hands-on experience leveraging large-scale data to build ML/DL models with Python
• PhD-level expertise in one or more of the following domains: Recommendation Systems, Natural Language Processing, Computer Vision, Speech and Audio, Time-series, Reinforcement Learning, Graph Learning
• A deep understanding of the ML development lifecycle and how to optimize the trade-offs in each step. 
• Proven track record of designing, implementing, optimizing and scaling performant AI-empowered applications. Solid experience with MLOps practices in order to operationalize and maintain those applications in production.
• Excellent communication and collaboration skills targeting a diverse audience from stakeholders to cross-functional technical teams, in order to provide technical guidance and insight.

• Expertise in genAI or agentic AI. Hands-on experience in prompt design, optimization, testing and evaluation for different types of foundational models.
• Familiarity with a wide range of big data technologies, such as Apache Spark, Delta Lake, Apache Kafka, Apache Flink and NoSQL databases.

We're looking for an AI expert who wants to be at the forefront of innovation in the iGaming industry. Join us in shaping the future of iGaming with breathtaking experiences that thrill and delight players around the world.

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
• 👨‍👩‍👧‍👦 Family Support.
• #Li-Remote

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

Are you passionate about working with the most cutting-edge technologies, including AI, big data analytics, LLMs, data mining, and business intelligence (BI)? Are you looking to become part of a world-class engineering team? Do you aspire to contribute to a globally recognized, pre-IPO leader in technology?

As a Senior Software Engineer, you will contribute to the design and development of AI-driven architectures that power our next-generation intelligent customer engagement platforms. Your contributions will help shape AI-powered customer experiences, enhancing the intelligence and efficiency of our service platforms.

Job Responsibilities:

• Develop and enhance a cloud-based data foundation system and AI agent platform. This involves leveraging AI/ML models, applying prompt engineering techniques, and conducting data analysis across structured, semi-structured, and unstructured data. Utilize technologies such as data and pattern mining, business intelligence (BI), and data transformation and processing.
• Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and business stakeholders, to deliver a high-performance, reliable, scalable service with assured AI quality.
• Contribute to architectural discussions, providing technical design input and ensuring alignment with the overall technology roadmap while adopting best practices effectively and independently.
• Participate in shaping the engineering roadmap, ensuring solutions are scalable and extensible while meeting business needs.
• Support and mentor junior engineers, fostering a collaborative and innovative development culture.
• Stay up-to-date with industry trends, emerging technologies, and advancements in AI and data engineering.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in backend development for cloud-based services, with a strong focus on scalability, reliability, and performance.
• Proficiency in Java, Python, C++, C#, Kotlin, Scala, or similar languages.
• Experience building and optimizing data-intensive services, including data processing, transformation, storage, and retrieval at scale.
• Strong problem-solving skills and ability to design scalable solutions for AI-driven services.
• Strong written and verbal English communication skills.
• Prior experience with data platforms and/or AI services is highly desirable.
• Experience working with distributed data platforms and modern data architectures, such as Apache Spark, Databricks, Kafka, Delta Lake, or similar is a desirable.
• Experience in data science and practical experience applying AI/ML models is a plus.

Additional Notes:
This position will follow a hybrid work model.

You

The Solution Architect is a technical and consultative leader who bridges the gap between client needs and the delivery of impactful solutions. As subject matter experts, they design scalable, maintainable, and reusable architectures that solve business challenges and support long-term goals.

Engaged from the sales cycle through project completion, Solution Architects collaborate with clients and internal teams to translate requirements into high-level solution designs, identify gaps in out-of-the-box offerings, and define actionable backlogs for engineering teams. They oversee multiple projects in parallel, ensuring solutions are globally applicable, performance-optimized, and built on reusable components.

While not involved in daily coding, Solution Architects review and guide technical deliverables to align with the architectural vision, troubleshoot issues, and implement performance optimizations. They also develop tools, modules, and utilities to improve delivery efficiency. Success in this role demands a strategic mindset, deep knowledge of Feedzai products and adjacent technologies, and the ability to align technical decisions with business objectives. By fostering innovation, championing best practices, and maintaining a client-first approach, Solution Architects reinforce Feedzai’s position as a trusted provider of sustainable and high-performing software solutions.

Your Day-to-Day

• Solution Design & Requirements Analysis: Translate client needs into high-level, scalable, and maintainable solution architectures. Create actionable development backlogs, addressing gaps in out-of-the-box solutions and ensuring alignment with client objectives.

• Product Fit & Implementation Excellence: Evaluate Feedzai’s product offerings to recommend the best fit for each client’s environment. Advise on implementation best practices for long-term success.

• Pre-Sales & Stakeholder Engagement: Support the sales cycle with technical expertise, present solutions to technical and non-technical audiences, and ensure proposals align with strategic objectives.

• Implementation Oversight & Quality Assurance: Guide project execution to match the architectural vision, reviewing deliverables for quality, performance, and scalability.

• Performance, Optimization & Troubleshooting: Design for performance, address issues promptly, and optimize cloud usage (AWS, Azure, GCP) for cost-effectiveness and scalability.

• Reusability & Continuous Improvement: Create reusable components, tools, and utilities to improve efficiency across projects and contribute to Feedzai’s technical practice improvements.

• Risk & Impact Management: Identify and mitigate technical risks while maintaining timelines and business goals.

• Cross-Functional Collaboration: Partner with engineering, product, and client success teams to align technical solutions with company strategy and ensure clear communication.

• Knowledge Sharing & Support: Mentor team members, promote a culture of innovation, and resolve Level 2 support issues to maintain client satisfaction.

You Have and you Know-How

• Bachelor’s degree in Computer Science, Engineering, or a related field, with at least 5 years of Java development experience and 2+ years in systems/solution design;

• Strong proficiency in Java and frameworks (Spring and Hibernate), with expertise in concurrent and distributed environments;

• Advanced skills in Java application performance tuning, including JVM optimization, memory management, and garbage collection;

• Proven experience designing scalable, high-performance enterprise systems;

• Hands-on experience with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes);

• In-depth knowledge of messaging systems (RabbitMQ, Kafka) and data processing frameworks (Spark, ELK);

• Deep understanding of relational databases (e.g., PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra), including performance tuning;

• Strong grasp of microservices architecture, RESTful APIs, and enterprise integration patterns;

• Knowledge of security best practices in system design, including data encryption, authentication, authorization, and secure communication;

• Proficiency in Agile methodologies, CI/CD practices, and DevOps tools (e.g., Jenkins, GitLab);

• Strong problem-solving abilities, system optimization skills, and excellent communication for collaboration with clients and technical teams.

#LI-Remote #LI-BX1

About this job

At JUMO, we’ve built a smart financial services platform to make finance accessible to everyone.  Our Data engineering team ensures that our intelligent banking platform is able to acquire data from millions of users across globally distributed sources, such as GSM. Beyond ingress, the data is processed and stored in the cloud to support event-driven analytics and machine learning pipelines.

As a JUMO Junior Data Engineer, you will design, build and maintain scalable data architectures.  You will monitor their performance, perform root cause analysis and provide solutions to any issues that might arise. You will work with large, complex data sets, which means experience working with Big Data is essential.  On a typical day, we use Spark, Kafka, Python, SQL, Airflow and AWS technologies, such as Redshift.  We work with Docker and Kubernetes for automating deployment, scaling, and management of containerized applications.  

You will

• Be responsible for creating robust, mission critical batch and streaming data processing capabilities
• Design, implement, and maintain the data pipelines that constitute JUMO's data platform, enabling effective use of data across the organisation
• Provide feedback on team members' output, encouraging skills development within the team
• Work closely with Portfolio Managers and Decision Scientists to understand the real world problems we’re trying to solve
• Be supported by senior leaders as you drive your own development

You will need

• BSc. in Computer Science, Electrical Engineering or equivalent tertiary degree
• Real-world understanding & experience of data pipeline design and development, as well as data processing and storage (i.e. experience in designing systems to process and curate large data sets)
• Experience in streaming technologies, specifically Spark and Kafka
• Experience with cloud technologies, AWS preferred
• Solid, proven experience working with big-data technologies such as Apache Spark, Flink, Hadoop, Kafka or Kinesis, DynamoDB
• Command of productionising and monitoring of data pipeline workflows, and working knowledge of the Data Product Lifecycle
• Experience in application design and development with at least one of the following languages: Python (preferred), Kotlin
• RDBMS experience in any relevant technology such as MySQL, PostgreSQL, Redshift and SQL Server.  This includes experience with relational database administration, technical architectures and infrastructure components
• Understanding of CI/CD practices
• Productive within a Linux command line environment
• Proven ability to contribute software as part of a team.  We are looking for someone that can effectively communicate technical concepts, and apply critical thinking under pressure

Bonus if you have

• Experience working with messaging systems (RabbitMQ, Redis, SNS)
• Experience working with data pipeline orchestration (Airflow, Nifi, Dagster )
• Experience working with production BI environments and tools (Tableau, Superset, Looker)

We ask a lot of each other at JUMO, but we give a lot too.

You will love

• Collaborating with smart, engaging people in an inspiring work environment
• Working for impact
• Growing and learning continuously, with loads of encouragement and support
• Boldly taking risks as we navigate new challenges
• Flexible work practices enabling your best delivery
• Being autonomous and empowered to lead
• A stack of leading-edge technologies

Remote First

We operate a remote first working approach, where working remotely is our default way of working. Our environment is designed to foster innovation and enable collaboration. You have flexibility where to work from (between time zone UTC 0 and UTC +3), as long as you are set up to work remotely and have access to data with a strong and reliable connection as we value online facetime for collaboration at JUMO.

Diversity and Inclusion

At JUMO, we firmly believe that diversity strengthens our teams. We are dedicated to fostering an inclusive recruitment process that cultivates an environment where all individuals can be authentic, collaborate, and thrive.

About this job

At JUMO, we’ve built a smart financial services platform to make finance accessible to everyone.  Our Data engineering team ensures that our intelligent banking platform is able to acquire data from millions of users across globally distributed sources, such as GSM. Beyond ingress, the data is processed and stored in the cloud to support event-driven analytics and machine learning pipelines.

As a JUMO Data Engineer, you will design, build and maintain scalable data architectures.  You will monitor their performance, perform root cause analysis and provide solutions to any issues that might arise. You will work with large, complex data sets, which means experience working with Big Data is essential.  On a typical day, we use Spark, Kafka, Python, SQL, Airflow and AWS technologies, such as Redshift.  We work with Docker and Kubernetes for automating deployment, scaling, and management of containerized applications.  

You will

• Be responsible for creating robust, mission critical batch and streaming data processing capabilities
• Design, implement, and maintain the data pipelines that constitute JUMO's data platform, enabling effective use of data across the organisation
• Provide feedback on team members' output, encouraging skills development within the team
• Work closely with Portfolio Managers and Decision Scientists to understand the real world problems we’re trying to solve
• Mentor juniors with technical leadership
• Be supported by senior leaders as you drive your own development

You will need

• BSc. in Computer Science, Electrical Engineering or equivalent tertiary degree
• Real-world understanding & experience of data pipeline design and development, as well as data processing and storage (i.e. experience in designing systems to process and curate large data sets)
• Experience in streaming technologies, specifically Spark and Kafka
• Experience with cloud technologies, AWS preferred
• Solid, proven experience working with big-data technologies such as Apache Spark, Flink, Hadoop, Kafka or Kinesis, DynamoDB
• Command of productionising and monitoring of data pipeline workflows, and working knowledge of the Data Product Lifecycle
• Experience in application design and development with at least one of the following languages: Python (preferred), Kotlin
• RDBMS experience in any relevant technology such as MySQL, PostgreSQL, Redshift and SQL Server.  This includes experience with relational database administration, technical architectures and infrastructure components
• Understanding of CI/CD practices
• Productive within a Linux command line environment
• Proven ability to contribute software as part of a team.  We are looking for someone that can effectively communicate technical concepts, and apply critical thinking under pressure

Bonus if you have

• Experience working with messaging systems (RabbitMQ, Redis, SNS)
• Experience working with data pipeline orchestration (Airflow, Nifi, Dagster )
• Experience working with production BI environments and tools (Tableau, Superset, Looker)

We ask a lot of each other at JUMO, but we give a lot too.

You will love

• Collaborating with smart, engaging people in an inspiring work environment
• Working for impact
• Growing and learning continuously, with loads of encouragement and support
• Boldly taking risks as we navigate new challenges
• Flexible work practices enabling your best delivery
• Being autonomous and empowered to lead
• A stack of leading-edge technologies

Remote First

We operate a remote first working approach, where working remotely is our default way of working. Our environment is designed to foster innovation and enable collaboration. You have flexibility where to work from (between time zone UTC 0 and UTC +3), as long as you are set up to work remotely and have access to data with a strong and reliable connection as we value online facetime for collaboration at JUMO.

Diversity and Inclusion

At JUMO, we firmly believe that diversity strengthens our teams. We are dedicated to fostering an inclusive recruitment process that cultivates an environment where all individuals can be authentic, collaborate, and thrive.

What Is The Role : 

Developers and community matter. Our users and contributors have helped ensure that the Elastic Stack (including Elasticsearch, Kibana, Beats, and Logstash) is more than just code — they are open source projects that people love to use.

We’re looking for someone who can connect with our global audience through creative, educational, and visually engaging content. You don’t need to be a Senior Engineer — but you should have a strong technical foundation, curiosity to learn, and the skills to tell compelling stories about technology.

Your work will combine writing, visuals, and video — with no waiting on others to get it done. From drafting a Twitter thread in the morning to publishing an infographic and editing a short video in the afternoon, you’ll take ideas from concept to launch, end to end.

What You Will Be Doing:

• Create engaging technical content for social media, blogs, and YouTube, covering Search, AI, and Elasticsearch in ways that are approachable and inspiring. Topics range from foundational and evergreen topics to today's LLM release.
• Write short-form content (Twitter threads, LinkedIn posts) that distills complex concepts into clear, shareable insights.
• Produce simple, high-quality videos and infographics yourself — from scripting and recording to editing and publishing.
• Explore new trends in Search, AI, and developer tools, and translate them into content our audience cares about.
• Build demos and examples to support your content or share the highlights of the latest research papers.
• Add a creative spark to Elastic’s content to keep our community engaged and draw in new audiences.

What You Bring : 

• Solid technical background and experience in an engineering role.
• Demonstrated ability to create a variety of content formats: blog posts, social media threads, videos, infographics.
• Comfortable working independently and seeing projects through from idea to publication without waiting on others.
• Curiosity and adaptability to quickly pick up new tools and topics.
• A collaborative mindset and willingness to share ideas, in a fully distributed team.
• Strong written and spoken communication skills in English.

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 

The Product Team builds our product to disrupt the RiskOps/financial crime industry from a data-led approach. We partner with our clients using a holistic lens and have result-driven solutions to manage financial risk with a cloud-first platform and a world-class user experience. Being part of this team, you have a voice in planning, strategizing, and challenging the status quo. Your thoughts and ideas are valued. Our fast-paced and open environment encourages us to lean in, try new things, and discover our potential. We define and act on what could be in tomorrow's world, not on what is today.

#LI-Remote #LI-MG3

We're a leading SaaS provider revolutionising how fintech companies navigate complex regulatory landscapes. Our platform powers compliance and risk management for hundreds of innovative financial services companies, from emerging startups to established enterprises. We believe in empowering our teams to solve meaningful problems and create exceptional value for our customers.

Role Summary

As a Senior Data Scientist at ComplyAdvantage, you will lead the development and refinement of sophisticated data-driven solutions to detect and prevent financial crime globally. Your core focus is R&D and Strategic Initiatives, where you will spend 80% of your time conducting forward-looking research in ML, NLP, and Agentic AI to create measurable business value over 3-6 month horizons. In addition to driving deep-dive R&D, you will provide expert advisory support and technical leadership to Product and Engineering teams. By leading AI Enablement workstreams, you will empower these departments with the quantitative insights and frameworks necessary to scale high-impact, AI-driven features while mentoring more junior members of the tribe.

Key Responsibilities

• Lead R&D in GenAI and Agentic AI: Design and prototype high-impact, novel solutions for financial crime detection, focusing on multi-agent systems and RAG architectures built on foundational LLM frameworks.
• Drive Production Excellence: Partner with Engineering and Product leadership to architect and oversee the integration of AI components into core product features. You will define the standards for reliability, scalability, and ethical AI performance, ensuring research prototypes transition into robust, production-grade solutions.
• Establish Evaluation Frameworks: Lead the development of robust evaluation methodologies for LLM and agentic AI systems, defining industry-standard metrics for task completion, reasoning accuracy, and system reliability.
• Evaluate Model Context Protocol (MCP): Research applications to connect our AI systems with external data sources and tools, providing strategic recommendations for engineering implementation.
• Strategic Data Insights: Conduct advanced exploratory analysis across multiple data sources to uncover insights that directly influence product development decisions and agent behavior.
• Research & Innovation: Continuously research and evaluate emerging tools and best practices in data science and Agentic AI to keep ComplyAdvantage at the forefront of the field.
• Technical Leadership & Mentoring: Engage across multi-disciplinary teams to share expertise, perform code reviews, and provide career development support to junior data scientists.

Required Qualifications

• MSc or PhD in a numerate subject (e.g., Computer Science, Mathematics, Statistics, Physics) or equivalent practical experience in a data-intensive role.
• 4-7 years of professional experience in data science or machine learning, with a demonstrable impact on production systems.
• Expert-level proficiency in Python, including the core data science ecosystem such as Pandas, NumPy, and Scikit-learn.
• Deep experience with modern ML frameworks (e.g., TensorFlow, PyTorch) for advanced research and prototyping.
• Strong expertise in Agentic AI and LLMs: Advanced knowledge of agentic AI frameworks (e.g., LangChain, Pydantic AI) and experience optimising retrieval systems like RAG.
• Experience with Distributed Computing: Practical knowledge of platforms like Spark or Dask for large-scale data analysis.
• Technical Leadership: Proven track record of leading technical research projects with successful production outcomes and communicating complex concepts to diverse audiences.

Preferred Qualifications

• Experience delivering machine learning solutions and integrating into data pipelines.
• Experience with Natural Language Processing, Entity Resolution, Graph Theory, or Graph Machine Learning.
• Experience working with or evaluating multi-agent systems or complex GenAI workflows.

What Success Looks Like

• In 90 days: You have successfully onboarded, mastered our data landscape, and begun contributing to active research projects while building relationships with key stakeholders.
• In 6 months: You have delivered your first significant research project with measurable impact and established yourself as a technical leader and effective mentor.
• In 12 months: You have led multiple successful R&D initiatives that have shaped our technical roadmap and been recognized as a subject matter expert who empowers other teams.

About Data Science at ComplyAdvantage:
The Data Science tribe discovers and proves out impactful solutions that leverage our Petabyte-scale data infrastructure to neutralise global financial crime. We are responsible for research and development work that drives the "art of the possible" within our product suite. At ComplyAdvantage, we mine the internet for critical data and use it to power a dynamic knowledge graph, which uncovers hidden networks of financial bad actors. From exploring real-time stream processing with Kafka to pioneering the use of the latest LLMs, our modern technology stack allows us to innovate and build prototypes for cutting-edge agentic AI and large-scale algorithmic solutions that empower our clients.

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 

We are looking for a driven and experienced Site Reliability Engineering Manager to join our innovative Tech Team. You will lead and empower a team of SREs, partnering closely with Engineering, Product, and Security to ensure our platforms are resilient, scalable, and secure. You will play a key role in shaping reliability strategy, improving system performance, and embedding best practices in observability, incident management, and automation to support the delivery of high-impact solutions in the fight against financial crime.

As a Site Reliability Engineering (SRE) Manager, you will:

• Take ownership of your team, being responsible for current team members’ growth and development, plus hiring and onboarding new team members
• Create a positive environment where your team members thrive to deliver the best outcomes and innovations
• Be a role model for your team, mentoring and coaching them, whilst having a learning mindset yourself, being open to new ideas and technologies
• Within the context of our broader technology vision, set the direction for your team and take accountability for tech decisions 
• Use your specific experience working with cloud systems to input into technical decision-making
• Work with other stakeholders across engineering to ensure the systems and services your team provides meet the needs of your internal customers
• Collaborate, both within your team and across the tribe to ensure your team’s implementation meets industry standards

The role reports to the Director of Infrastructure. You’ll be managing a team of Engineers focused on the provision and support of our Stateful / Data layer technologies powering all of our services, both in development and production. The main technologies we use are YugaByte (sharded Postgres), Kafka (via Strimzi), Elasticsearch (via ECK), Redis and Spark/data warehousing on GCP and AWS using their PaaS systems. As the technology stack underpins all other engineering work, a collaborative mindset is a must.

Our tech stack:

ComplyAdvantage is fully cloud-based, with a modern kubernetes-focused tech stack. All compute workloads run in Kubernetes, with clusters in multiple regions to support the needs of our global client base. Our production services are multi-cloud by design and are currently hosted in AWS and GCP.

We make heavy use of Terraform and Helm to define our infrastructure and services, and lean heavily on GitOps paradigms - production and non-production environments are defined in git and changes to these environments (both cloud infrastructure and Kubernetes applications) are managed via git.

ArgoCD is our tool of choice for controlling our deployments, and paired with our Istio mesh, allows us for advanced deployment patterns used by our development teams such a progressive rollouts. Our observability stack consists of Grafana Cloud, along with some on-prem Mimir, amongst others. We focus on Open Telemetry for application metrics, with SLO and metric driven alerting at all levels, from Cloud infra through to application performance.

Across the wider Technology team, teams build and release containerised applications to support the wide array of activities that our teams are engaged in - from developing low latency client-facing APIs, to machine learning models and data processing pipelines.

About you:

As an Site Reliability Engineering (SRE) Manager, you will

• Have experience of managing and growing high performing engineering teams
• Have experience with Kubernetes and Terraform
• Have experience hosting microservices-based architectures
• Have experience of working with cloud native architectures (AWS and GCP are preferred)
• Have good communication and writing skills including experience writing technical documentation

Nice to haves:

• Experience of working in a start-up/ scale-up environment
• Have experience managing observability platforms, whether self-hosted or third party - eg Grafana stack, Datadog, NewRelic
• Have experience managing pipeline tools, whether self-hosted or third party - eg CircleCI, ArgoCD, Harness, etc

Benefits:

• 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 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 

Role Summary

As a Data Scientist at ComplyAdvantage, you will develop and refine data-driven solutions to detect and prevent financial crime globally. Your core focus is R&D and Strategic Initiatives, conducting forward-looking research in ML, NLP, and Agentic AI to create measurable business value. In addition to deep-dive R&D, you will provide advisory support to Product and Engineering teams. By investing in AI Enablement workstreams, you will empower these departments with the quantitative insights and frameworks necessary to scale high-impact, AI-driven features.

Key Responsibilities

• Advance R&D in GenAI and Agentic AI: Develop high-impact prototypes for financial crime detection, leveraging multi-agent systems and RAG architectures built on foundational LLM frameworks.
• Contribute to Core Solutions: Collaborate with Engineering and Product to integrate and optimise AI components and frameworks into existing and new product features, ensuring reliability, scalability, and ethical performance in production.
• Evaluate LLM-based Systems: Contribute to the development and implementation of robust evaluation methodologies for LLM and agentic AI based systems, tracking key metrics related to task completion, reasoning accuracy, tool effectiveness, and overall reliability.
• Evaluate Model Context Protocol (MCP) applications: Connect our AI systems with external data sources and tools and provide recommendations for engineering implementation
• Data Understanding: Develop a solid understanding of our existing data sources, identifying challenges and suggesting potential improvements.
• Data Analysis: Use exploratory data analysis and data mining techniques to identify actionable insights for product improvement, including patterns that can inform and refine agent behavior and prompt engineering strategies.
• Research & Innovation: Continuously research and evaluate emerging tools, technologies, and best practices in data science, especially within the rapidly evolving field of Agentic AI, to keep ComplyAdvantage at the forefront.
• Cross-Functional Collaboration: Engage effectively with multi-disciplinary teams to actively share best practices, expertise and inspire innovation to foster an AI-first culture across the organization.
• Visualization & Roadmapping: Provide clear data insights and visualizations that will act as a basis for new ideas to be integrated into our product roadmap.

Required Qualifications

• MSc or PhD in a numerate subject (e.g., Computer Science, Mathematics, Statistics, Physics) or equivalent practical experience in a data-intensive role.
• 2-4 years of professional experience in data science or a related field, with a demonstrated ability to contribute to impactful data-driven solutions.
• Proficiency in Python, including experience with core data science libraries (e.g., Pandas, NumPy, Scikit-learn).
• Hands-on experience with modern machine learning frameworks such as TensorFlow or PyTorch.
• Familiarity with the foundational concepts of agentic AI and large language models (LLMs). This can be professional or through personal research.
• Basic understanding of popular agentic AI frameworks (e.g., LangChain, Pydantic AI).
• Knowledge of general evaluation techniques for AI models and an eagerness to learn and apply methods specific to agentic systems.
• Ability to communicate complex technical concepts effectively to a variety of stakeholders.
• Strong passion for data and solving challenging real-world problems using algorithms.

Preferred Qualifications

• Prior experience contributing to the deployment and integration of machine learning models into production data pipelines.
• Exposure to Big Data platforms such as Spark.
• Experience with Natural Language Processing, Entity Resolution, Graph Theory, or Graph Machine Learning.
• Experience working with or evaluating multi-agent systems or complex AI workflows.

What Success Looks Like

• In 90 days: You have successfully onboarded, gaining a clear understanding of our data landscape and current AI frameworks. You are actively contributing to R&D experiments and have established collaborative working relationships with peers in Engineering and Product.
• In 6 months: You have delivered your first significant R&D prototype or technical evaluation. You have begun contributing to our AI Enablement workstreams, perhaps by authoring a technical blog post or internal guide that translates your research findings into actionable knowledge for the wider team.
• In 12 months: You have completed multiple R&D initiatives that have shaped our technical roadmap. You are recognized for empowering other teams through your advisory support and quantitative expertise, consistently providing the "AI-first" insights that help Engineering and Product teams scale high-impact features.

About Data Science at ComplyAdvantage:
The Data Science tribe discovers and proves out impactful solutions that leverage our Petabyte-scale data infrastructure to neutralise global financial crime. We are responsible for research and development work that drives the "art of the possible" within our product suite. At ComplyAdvantage, we mine the internet for critical data and use it to power a dynamic knowledge graph, which uncovers hidden networks of financial bad actors. From exploring real-time stream processing with Kafka to pioneering the use of the latest LLMs, our modern technology stack allows us to innovate and build prototypes for cutting-edge agentic AI and large-scale algorithmic solutions that empower our clients.

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