Senior ML Engineer — Remote, Production-Ready FinData

FullStack; Austin (TX); Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Remote work

Health insurance

401(k) match

Paid time off

Job summary

FullStack is seeking a Senior Machine Learning Engineer to join our team. You’ll work with our incredible clients in a fully remote setup, delivering traditional ML solutions and production-ready data pipelines that power AI initiatives across the Americas.

You will contribute to both client-side augmentation and internal product teams, applying advanced ML techniques, data preprocessing, and feature engineering to solve real-world problems with a focus on reliability and scalability.

Qualifications

• 5+ years of professional experience in software development, Data Science, or Machine Learning Engineering.
• Advanced English is required.
• Successful completion of a four-year college degree is required.
• Strong expertise in traditional machine learning algorithms and statistical modeling, with a focus on non-LLM and non-Generative AI approaches.
• Hands-on experience designing, developing, training, and optimizing machine learning models for production use.

Responsibilities

• Work on Team Augmentation: integrate into client teams and collaborate with designers and engineers daily.
• Work on Design & Build: contribute to a FullStack product team delivering ML-enabled solutions.

Skills

Python

Machine Learning

Data Science

Anomaly detection

Production ML

Agile/Scrum

SQL

CI/CD

Financial datasets

Team collaboration

Education

Bachelor's degree

Tools

Pandas

NumPy

scikit-learn

TensorFlow

PyTorch

Job description

FullStack is seeking a Senior Machine Learning Engineer to join our team. You’ll work with our incredible clients in a fully remote setup, delivering traditional ML solutions and production-ready data pipelines that power AI initiatives across the Americas.

You will contribute to both client-side augmentation and internal product teams, applying advanced ML techniques, data preprocessing, and feature engineering to solve real-world problems with a focus on reliability and scalability.