Senior Machine Learning Engineer

Maxana; Chicago (IL); Remote; USD 100,000 - 150,000; Full time

Job summary

Maxana seeks a skilled Machine Learning Engineer to join our team, serving a Fortune 500 client. This role focuses on developing and optimizing machine learning models to streamline data-driven decision-making and enhance payment systems. Candidates should have extensive experience in model deployment, programming, and collaboration with cross-functional teams, contributing to innovative solutions in the financial services sector. Enjoy a fully remote work environment, competitive pay, and extensive benefits.

Benefits

Competitive pay

Extensive health coverage and life insurance

401(K) plan

Qualifications

• 5+ years of experience in building and deploying ML models in production.
• Strong programming skills in Python with ML frameworks.
• Experience in financial system modeling and distributed computing.

Responsibilities

• Develop and optimize ML models for business solutions.
• Work with data teams to integrate models into applications.
• Monitor and improve model performance in production.

Skills

Machine Learning

Python

Feature Engineering

Model Deployment

Data Quality

Data Pipeline Optimization

Education

Bachelor's degree in Computer Science

PhD in Machine Learning (preferred)

Tools

PyTorch

TensorFlow

scikit-learn

Spark

Job description

Maxana is on the lookout for a skilled Machine Learning Engineer to join our innovative team, that will be supporting our fortune 500 client. In this role, you will be responsible for designing and implementing machine learning models and algorithms that will drive our data-driven decision-making processes. You will work closely with data scientists, software engineers, and product teams to integrate machine learning solutions into our applications, ensuring they meet 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
• Conduct experiments to evaluate and improve model performance
• Stay up-to-date with the latest developments in machine learning technologies and methodologies
• Document processes, code, and model deployments for team knowledge sharing
• Monitor and troubleshoot model performance in production
• Communicate results and insights to stakeholders effectively
• Design, develop, and deploy LLM that improve payment success rates, reduce fraud, and optimize payment routing across our global platform
• Build robust data pipelines and feature engineering systems to support model training and inference at scale
• Collaborate 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 continuously iterate to improve model accuracy and business impact
• Mentor junior team members and contribute to the technical direction of the payment modeling team
• Stay current with the latest research and advances in machine learning, especially in areas relevant to financial services and payment processing
• Translate complex technical concepts to non-technical stakeholders and communicate model insights effectively

• Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or related technical field
• 5+ years of professional experience building and deploying machine learning models in production environments
• Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Experience with building and optimizing data pipelines and workflows using tools like Spark, Airflow, or similar technologies
• Deep LLM expertise
• Demonstrated expertise in feature engineering, model selection, and hyperparameter tuning
• Strong understanding of payment systems, financial transaction processing, or risk modeling
• Experience working with large datasets and distributed computing platforms
• Knowledge of software engineering best practices including version control, testing, and CI/CD

Preferred

• PhD in Machine Learning, Data Science, or related field

• Experience with fraud detection, anomaly detection, or risk modeling in financial services

• Knowledge of time series forecasting, graph neural networks, or reinforcement learning

• Familiarity with regulatory considerations in payment processing across different regions

• Experience with real-time prediction systems and model serving infrastructure

• Contributions to the ML community through publications, open-source projects, or conference presentations

• Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies

• 100% Remote
• Competitive pay
• Extensive health coverage and life insurance
• 401(K) plan