Machine Learning Engineer (Python)
We are seeking a hands-on Machine Learning Engineer to support and enhance a portfolio of existing machine learning models at different stages of maturity. The engineer will collaborate closely with the current team across model development, testing, optimization, and deployment. This role is particularly suited to someone comfortable working with data, improving predictive models, and transforming experimental notebooks into structured, maintainable, production-ready Python code. The team will provide guidance on the models, development priorities, testing approach, and deployment process.
**This is a 3-month contract, with extension to 6 months based on performance.
Key Responsibilities:
Prepare, clean, transform, and validate datasets for model development.
Identify and engineer meaningful features based on available data and business requirements.
Support the development and enhancement of machine learning models.
Work with techniques such as multivariate regression and gradient boosting.
Evaluate model performance and contribute to model testing and validation.
Refactor notebooks into reusable, modular Python functions, scripts, and packages.
Help move models through development, testing, and productionization stages.
Work with data stored and processed through SQL and Snowflake.
Support model-related workflows across AWS and Azure DevOps.
Follow and improve the team’s existing in-house MLOps practices.
Participate in daily stand-ups and collaborate with technical and business stakeholders.
Complete assigned improvements and demonstrate delivered functionality.
Document model logic, technical decisions, testing results, and implementation changes.
Required Skillset:
Strong hands-on experience with Python for data science or machine learning.
Proficiency with pandas for data manipulation and analysis.
Practical SQL experience, including data extraction, transformation, and validation.
Experience developing, enhancing, or maintaining machine learning models.
Knowledge of feature engineering and data preparation techniques.
Experience with regression-based models and gradient-boosting algorithms.
Ability to convert exploratory notebooks into modular, maintainable Python code.
Experience testing models and supporting their transition toward production.
Strong communication, collaboration, and technical documentation skills.
Availability to maintain sufficient working-hour overlap with the North Carolina team.
Preferred Qualifications
Experience working with Snowflake.
Exposure to AWS services used in data or machine learning workflows.
Experience with Azure DevOps for source control, work tracking, or CI/CD.
Familiarity with MLOps principles and model lifecycle practices.
Experience supporting multiple models at different maturity levels.
Previous experience working as part of a distributed or nearshore team.
Benefits we offer
Access to e-Learning platforms.
Access to a virtual nutritionist
Amazing people oriented organizational culture
Working from anywhere
Challenging projects using the latest technologies with clients from the US.