Senior Machine Learning Engineer

Summary

Join Trustly's Data Science team as a Senior Machine Learning Engineer and play a key role in developing and deploying machine learning models for transactional risk and fraud assessment. You will collaborate with Data Scientists, MLOps, and DataOps teams to build and optimize models, ensuring efficient and scalable workflows. Responsibilities include model development and optimization, data exploration and feature engineering, productionization of ML models, monitoring and maintenance, scalable system design, innovation, and collaborative problem-solving. This role requires a Bachelor's or Master's degree in a technical field, solid experience in DS/ML engineering, proficiency in programming languages, and experience with AWS cloud services and CI/CD pipelines. The ideal candidate will also possess experience with machine learning modeling, online inference, and working with imbalanced datasets. Trustly offers a remote-first culture with various benefits, including health and dental insurance, life insurance, meal and supermarket vouchers, home office allowance, and more.

Requirements

• 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

Responsibilities

• Design the data-architecture flow for the efficient implementation of real-time model endpoints and/or batch solutions
• Engineer domain-specific features that can enhance model performance and robustness
• 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
• 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
• 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
• Conduct research and prototypes to explore novel approaches in ML engineering for addressing emerging risk/fraud patterns
• Partner with fraud analysts, risk managers, and product teams to translate business requirements into ML solutions

Preferred Qualifications

• 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)

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!