Senior Machine Learning Engineer

Maxana is seeking a skilled Machine Learning Engineer to join our innovative team supporting a Fortune 500 client. In this role, you will be responsible for designing and implementing machine learning models and algorithms that drive data-driven decision-making within the payment and financial teams. You will collaborate with fellow MLEs, data scientists, software engineers, and product teams to integrate machine learning solutions into our applications, ensuring alignment with business and technical requirements. Responsibilities Develop, implement, and optimize machine learning models to solve complex business problems Collaborate with data scientists and software developers to integrate models into production systems Analyze and preprocess large datasets, ensuring data quality and integrity Design, develop, and deploy large language models (LLMs) to improve payment success rates, reduce fraud, and optimize payment routing across our global platform Develop generative AI solutions Build robust data pipelines and feature engineering systems to support model training and inference at scale Work with cross-functional teams including product managers, engineers, data scientists, and business stakeholders to identify opportunities and implement ML solutions Monitor model performance, analyze results, and iterate to enhance accuracy and business impact Stay updated with the latest research and advances in machine learning, especially in financial services and payment processing Translate complex technical concepts for non-technical stakeholders and communicate insights effectively Requirements Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or related fields 5+ years of experience deploying machine learning models in production Strong programming skills in Python and experience with ML frameworks like PyTorch, TensorFlow, or scikit-learn Experience with building and optimizing data pipelines using tools like Spark, Airflow, or similar Expertise in large language models (LLMs) Proficiency in feature engineering, model selection, and hyperparameter tuning Understanding of payment systems, financial transactions, or risk modeling Experience with large datasets and distributed computing platforms Knowledge of software engineering best practices including version control, testing, and CI/CD PhD in Machine Learning, Data Science, or related fields Experience with fraud detection, anomaly detection, or risk modeling in finance Knowledge of time series forecasting, graph neural networks, or reinforcement learning Familiarity with regulatory considerations in regional payment processing Experience with real-time prediction systems and model deployment infrastructure Contributions to ML community through publications, open-source projects, or conferences Experience with cloud platforms (AWS, GCP, Azure) and containerization Benefits 100% Remote Competitive pay Extensive health coverage and life insurance 401(K) plan

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