Remote Fintech ML Engineer: Risk & Automation

Kenmore Design LLC; Village of Kenmore (NY); Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Remote-friendly work environment

Flexible work arrangements

Job summary

Kenmore Design LLC is seeking a Machine Learning Engineer to own intelligent systems that analyze trading behavior, automate decisions, and deliver risk and performance insights for brokers and prop firms. You will work on real-world trading data and collaborate with product, risk, and engineering teams to turn complex financial data into actionable outputs.

Responsibilities include designing ML models for automation, processing large datasets, and integrating ML outputs into production systems.

Qualifications

• Proven experience as ML Engineer or Data Scientist in finance or related field.
• Experience with large datasets and time-series data.
• Strong Python or similar ML-focused language skills.
• Experience with data processing, feature engineering, and model evaluation.
• Understanding of financial or trading data structures is a plus.

Responsibilities

• Design and implement ML models for smart automation and analytics.
• Work with large datasets including historical trading data and account behavior.
• Develop models for risk calculations, performance analysis, and anomaly detection.
• Support automation workflows to improve client operational efficiency.
• Collaborate with engineering to integrate ML outputs into production systems.
• Translate analytical results into clear outputs for internal teams and clients.
• Stay current with ML techniques for financial data and time-series analysis.

Skills

Machine Learning

Time-series data

Python

Data processing

Feature engineering

Model evaluation

Job description

Kenmore Design LLC is seeking a Machine Learning Engineer to own intelligent systems that analyze trading behavior, automate decisions, and deliver risk and performance insights for brokers and prop firms. You will work on real-world trading data and collaborate with product, risk, and engineering teams to turn complex financial data into actionable outputs.

Responsibilities include designing ML models for automation, processing large datasets, and integrating ML outputs into production systems.