Senior ML Engineer - Remote, Production ML for Finance

FullStack; New Mexico; Remote; USD 130,000 - 190,000; Full time

Benefits offered by this job

Competitive Salary

Paid Time Off

100% remote work

401(k) with 4% match

Career advancement

Job summary

FullStack is seeking a Senior Machine Learning Engineer to join our team. You will work with top clients in a team augmentation or design-and-build capacity, applying traditional ML and statistical modeling to financial data and production-ready pipelines.

The role emphasizes hands-on model development, data exploration, feature engineering, and deployment in Agile environments. Strong English, a four-year degree, and a passion for ownership are essential.

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.
• Strong proficiency in data exploration, preprocessing, feature engineering, and model training using complex datasets.
• Experience analyzing financial, payroll, or other structured business datasets is highly preferred.
• Proactive, ownership-driven mindset with strong analytical and problem-solving skills.

Responsibilities

• Integrate into client teams and work daily with designers and engineers on project delivery.
• Design, build, and deploy ML solutions for production use within FullStack products.

Skills

Traditional ML

Python

Data exploration

Feature engineering

Anomaly detection

Agile/Scrum

Production ML

Financial datasets

Education

Four-year college degree

Tools

Scikit-learn

Pandas

NumPy

Job description

FullStack is seeking a Senior Machine Learning Engineer to join our team. You will work with top clients in a team augmentation or design-and-build capacity, applying traditional ML and statistical modeling to financial data and production-ready pipelines.

The role emphasizes hands-on model development, data exploration, feature engineering, and deployment in Agile environments. Strong English, a four-year degree, and a passion for ownership are essential.