Job Specifications
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Machine Learning Engineer in the Americas.
As a Senior Machine Learning Engineer, you will play a critical role in building scalable and efficient ML solutions that support risk assessment and fraud detection for high-volume financial transactions. You'll collaborate closely with Data Scientists, MLOps, and DataOps teams to implement production-grade models, optimize feature engineering, and monitor system performance. This position offers the opportunity to influence end-to-end machine learning workflows, contribute to real-time and batch processing architectures, and explore innovative approaches to emerging financial risks. You will thrive in a fast-paced, remote-first environment that values technical excellence, continuous learning, and cross-functional collaboration.
Accountabilities
Design, implement, and optimize machine learning models for production, supporting real-time and batch workflows
Engineer domain-specific features to enhance model robustness and predictive accuracy
Develop scalable pipelines for deploying, monitoring, and retraining ML models in production
Build architectures optimized for latency, throughput, and resource efficiency, adhering to reliability and security standards
Monitor model endpoints, pipeline performance, and key business metrics; implement recalibration and retraining as needed
Collaborate with fraud analysts, risk managers, and product teams to translate business requirements into ML solutions
Conduct research and prototypes to explore innovative ML approaches for emerging risk and fraud patterns
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related technical fields
Strong experience in ML engineering and data science implementation
Proficiency in Python, Scala, or Java
Hands-on experience with batch and real-time streaming pipelines using SQL and NoSQL databases
Familiarity with monitoring tools for pipelines, streaming systems, and model performance
Experience with AWS cloud services (Sagemaker, EC2, EMR, ECS/EKS, RDS, etc.)
Knowledge of CI/CD pipelines, infrastructure-as-code tools (Terraform, CloudFormation), and MLOps platforms such as MLflow
Expertise in machine learning modeling, especially tree-based and boosting algorithms for imbalanced targets
Experience with online inference systems, APIs, and latency-sensitive services
Strong proficiency in English
Preferred/Plus:
ML applications in financial decision-making (credit risk, fraud prevention)
AWS Sagemaker or similar DS/ML workbench experience
Containerization and orchestration (Docker, Kubernetes)
Feature store development and integration
Distributed data systems (Kafka, Spark, Hadoop) and workflow orchestration tools (e.g., Airflow)
Benefits
Comprehensive health and dental coverage for you and your dependents, no co-payment
Life insurance with extended coverage options
Meal and supermarket vouchers, home office allowance, and team allowance
Access to Wellhub for physical and online fitness activities
Trustly Club discounts at partner institutions and stores
English language online program with a private teacher
Extended maternity and paternity leave, plus birthday off
Flexible hours and fully remote work across Brazil
Apple equipment (MacBook Pro, iPhone) and welcome kit
Annual performance-based bonus
Employee referral program with rewards
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Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.
When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
It compares your profile to the job's core requirements and past success factors to determine your match score.
Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.
The process is transparent, skills-based, and free of bias -- focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.
Thank you for your interest!
About the Company
Your future of work, like you've always dreamt it, is now possible with Jobgether !
The Covid crisis has accelerated its revolution but work, as we knew it, doesn't exist anymore.
Tomorrow, jobs will be hybrid, remote and asynchronous. Flexibility will be the norm.
Jobgether helps you find your next remote job, wherever you are.
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