Senior Machine Learning Engineer

Remote

Full-time

Job Description

WHO WE ARE

At Trustly, we're building a smarter, faster, and more secure financial future by revolutionizing the world of payments. As a global leader in Open Banking Payments, we are establishing Pay by Bank as the new standard at checkout, providing unparalleled freedom, speed, and ease to millions of consumers and merchants worldwide.

Our Ambition: To build the world’s most disruptive payment network and redefine what the payment experience should feel like.

Trustly is a global team of innovators, collaborators, and doers. If you are driven by a strong sense of purpose and thrive in a dynamic, entrepreneurial, and high-growth environment, join us and be part of a team that’s transforming the way the world pays.

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;

Team Allowance;

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

Trustly Club - Discount at educational institutions and partner stores;

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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