Senior ML Engineer: Financial Data & Production, Remote

FullStack Labs, Inc.; Harrisburg (Dauphin County); Remote; USD 130,000 - 180,000; Full time

Benefits offered by this job

Health, dental, vision insurance

401(k) with 4% match

Paid time off

Job summary

FullStack Labs, Inc. is seeking a Senior Machine Learning Engineer (Traditional ML & Financial Data) to join our remote US team.

You will work with clients either by integrating into their teams or on a FullStack product team to build and deploy production‑grade ML solutions. The ideal candidate has 5+ years of software/data experience, a four-year degree, advanced English, strong Python skills, and a track record with traditional ML methods, data preprocessing, feature engineering, and anomaly

Qualifications

• 5+ years of professional experience in software development, data science, or ML engineering.
• Advanced English is required.
• A four-year college degree is required.
• Strong expertise in traditional machine learning algorithms and statistical modeling.
• Hands-on experience deploying ML models to production.
• Strong Python skills and ML/data science libraries.
• Experience with financial or structured datasets is highly preferred.

Responsibilities

• Design, train, and optimize ML models for production use.
• Explore data, preprocess, and engineer features for model training.
• Develop and optimize anomaly detection algorithms.
• Work in Agile/Scrum teams and maintain CI/CD for apps.
• Translate complex data into reliable ML solutions.

Skills

5+ years exp

Advanced English

Python

Agile/Scrum

Data exploration

Feature engineering

Anomaly detection

ML production

Financial datasets

Traditional ML

Ownership mindset

Education

Bachelor's degree

Tools

ML libraries

Job description

FullStack Labs, Inc. is seeking a Senior Machine Learning Engineer (Traditional ML & Financial Data) to join our remote US team.

You will work with clients either by integrating into their teams or on a FullStack product team to build and deploy production‑grade ML solutions. The ideal candidate has 5+ years of software/data experience, a four-year degree, advanced English, strong Python skills, and a track record with traditional ML methods, data preprocessing, feature engineering, and anomaly