Senior ML Engineer - Remote Production ML for Financial Data

FullStack; Augusta (ME); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive Salary

Paid Time Off (vacation, sick leave, U

100% remote work

Health, dental, and vision insurance

401(k) w/ 4% match

Ample opportunity for career growth

Job summary

FullStack is seeking a Senior Machine Learning Engineer to join our AI-enabled engineering team. You will work on production-ready ML systems, focusing on traditional ML and financial data, either by integrating into client teams or building product features.

Ideal candidates have 5+ years in software/data science, a four-year degree, strong Python, and experience with anomaly detection and scalable pipelines.

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 proficiency in data exploration, preprocessing, feature engineering, and model training using complex datasets.
• Hands-on experience designing, developing, training, and optimizing machine learning models for production use.
• Demonstrated experience developing and optimizing anomaly detection algorithms to identify irregularities, patterns, and outliers in data.
• Strong Python skills and experience with relevant machine learning and data science libraries.
• Experience analyzing financial, payroll, or other structured business datasets is highly preferred.

Responsibilities

• Team Augmentation: you will integrate into our client's team and work alongside their designers and engineers daily.
• Design & Build: you will work on a FullStack product team to build and deliver a product to our clients.

Skills

Machine Learning

Python

Data analysis

Agile/Scrum

English proficiency

Data exploration

Feature engineering

Education

Bachelor's degree

Job description

FullStack is seeking a Senior Machine Learning Engineer to join our AI-enabled engineering team. You will work on production-ready ML systems, focusing on traditional ML and financial data, either by integrating into client teams or building product features.

Ideal candidates have 5+ years in software/data science, a four-year degree, strong Python, and experience with anomaly detection and scalable pipelines.