Offer summary

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related technical field., Solid experience in Data Science and Machine Learning engineering., Proficiency in programming languages such as Python, Scala, or Java., Experience with AWS cloud services and CI/CD pipelines..

Key responsabilities:

Design and optimize data architecture for real-time model endpoints and batch solutions.

Engineer domain-specific features to enhance model performance.

Build and deploy machine learning models in production, ensuring scalability and efficiency.

Monitor model performance and implement systems for model retraining and recalibration.

Job description

WHO WE ARE

At Trustly, we’re on a mission to deliver a better way to pay and get paid. Consumers deserve a payment option that prioritizes financial responsibility, and merchants should have the independence to accept payments without unnecessary costs. This mission drives everything we do.

We’re revolutionizing the payments industry by making Pay by Bank the new standard at checkout, providing a smarter payment option to credit and debit cards. For merchants and consumers, this means the freedom to make and receive payments with greater security and ease.

Fueled by this purpose, we’ve grown into a global network connecting 9,000 merchants to 650 million consumers through 12,000 banks across 33 countries, processing over $58 billion annually. As the leader in Pay by Bank, we aim to redefine the payments experience by delivering exceptional products and unmatched value.

With regional offices in Vitória, Brazil and Silicon Valley, USA, and our global headquarters in Stockholm, Sweden, we are a diverse team that spans over 30 nationalities. Embracing a culture of innovation and collaboration, our 'work from anywhere' policy allows employees in Brazil, the U.S., and Canada to work remotely within their country of residence, enabling flexibility while staying connected to our global team.

At Trustly, we believe that inclusion and diversity are essential foundations for building a fair and equitable society. We do not discriminate based on race, religion, ancestry, color, national origin, gender identity, sexual orientation, age, citizenship, marital status, or disability status. Our main goal is to provide a fair, welcoming, diverse environment with opportunities for all collaborators. The stages of our selection process take place online and without distinction of any kind.

Now is the perfect time to join us and help accomplish our mission. If you’re inspired by purpose, thrive in a fast-paced and entrepreneurial environment, and are ready to shape the future of payments, we’d love to hear from you!

About the role

We are seeking a skilled and go-getter Sr. Machine Learning Engineer to join our Data Science team and play a pivotal role in driving the model development/production lifecycle. The ideal candidate will collaborate closely with Data Scientists, MLOps, and DataOps teams to implement ML models for assessing transactional risk and fraud, enable automated model retraining, and support robust machine learning inference systems. This role is essential for ensuring efficient, reliable, and scalable workflows to power data-driven insights and machine learning solutions.

What you will do:

Model Development and Optimization: Design the data-architecture flow for the efficient implementation of real-time model endpoints and/or batch solutions.

Data Exploration and Feature Engineering: Engineer domain-specific features that can enhance model performance and robustness.

Productionization of ML Models: Build pipelines to deploy machine learning models in production with a focus on scalability and efficiency, and participate in and enforce the release management process for models and rules.

Monitoring, Maintenance & Improvement: Implement systems to monitor model performance, endpoints/feature health, and other business metrics; Create model-retraining pipelines to boost performance, based on monitoring metrics; Model recalibration.

Scalable System Design: Design and implement scalable architectures to support real-time/batch solutions; Optimize algorithms and workflows for latency, throughput, and resource efficiency; Ensure systems adhere to company standards for reliability and security.

Innovation and Continuous Improvement: Conduct research and prototypes to explore novel approaches in ML engineering for addressing emerging risk/fraud patterns.

Collaborative Problem Solving: Partner with fraud analysts, risk managers, and product teams to translate business requirements into ML solutions.

Who you are:

Bachelor’s or Master’s degree in CS/Engineering/Data-Science or other technical disciplines.

Solid experience in DS/ML engineering.

Proficiency in programming languages such as Python, Scala, or Java.

Hands-on experience in implementing batch and real-time streaming pipelines, using SQL and NoSQL database solutions

Familiarity with monitoring tools for data pipelines, streaming systems, and model performance.

Experience in AWS cloud services (Sagemaker, EC2, EMR, ECS/EKS, RDS, etc.).

Experience with CI/CD pipelines, infrastructure-as-code tools (e.g., Terraform, CloudFormation), and MLOps platforms like MLflow.

Experience with Machine Learning modeling, notably tree-based and boosting models supervised learning for imbalanced target scenarios.

Experience with Online Inference, APIs, and services that respond under tight time constraints.

Proficiency in English.

It will be a "plus" if you have:

Prior experience with ML applied to financial decision-making, such as credit risk, and fraud prevention.

Prior experience with AWS Sagemaker and/or similar DS/ML workbench.

Proficiency in containerization and orchestration tools such as Docker and Kubernetes.

Feature store development and integration experience.

Experience with distributed data systems such as Kafka, Spark, Hadoop, and workflow/data orchestration tools (e.g., Airflow).

Our perks and benefits:

Bradesco health and dental plan, for you and your dependents, with no co-payment cost;

Life insurance with differentiated coverage;

Meal voucher and supermarket voucher;

Home Office Allowance;

Wellhub - Platform that gives access to spaces for physical activities and online classes;

Trustly Club - Discount at educational institutions and partner stores;

Monthly happy hours with iFood coupon;

English Program - Online group classes with a private teacher;

Extended maternity and paternity leave;

Birthday Off;

Flexible hours/Home Office - our culture is remote-first! You can work in every city in Brazil;

Welcome Kit - We work with Apple equipment (Macbook Pro, iPhone) and we send many more treats! Spoiler alert: Equipment can be purchased by you according to internal criteria!;

Annual premium - As a member of our team, you are eligible to receive an annual bonus, at the company's discretion, based on the achievement of our KPIs and individual performance;

Referral Program - If you refer a candidate and we hire the person, you will receive a reward for that!

Check out our Glassdoor or our Brazil Life page on Linkedin for more details about Brazil, our culture, and much more.

#LI-Remote

#LI-CHERRYNE-TRUSTLY

At Trustly, we embrace and celebrate diversity of all forms and the value it brings to our employees and customers. We are proud and committed to being an Equal Opportunity Employer and believe an open and inclusive environment enables people to do their best work. All decisions regarding hiring, advancement, and any other aspects of employment are made solely on the basis of qualifications, merit, and business need.

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