Remote ML Platform Engineer — Production‑Ready Pipelines

Sunthetics; San Marcos (TX); Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Equity

Health benefits

Promotion opportunities

Small team

Fully remote team

Job summary

Sunthetics is seeking a Machine Learning Engineer (Infrastructure Focus) to strengthen and streamline our ML and Bayesian Optimization package development. You will build robust, production-ready workflows, improve testing and reproducibility, and collaborate with data science, MLOps, and software teams.

The role emphasizes test automation, model versioning, CI/CD for ML, and maintaining connector layers between ML modules and the platform, with a fully remote team.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Math, or related field.
• 3+ years of experience in ML or backend software engineering.
• Strong Python engineering background, including Pytest, Pydantic, and modular package design.
• Hands-on experience with ML frameworks (especially PyTorch, BoTorch, Optuna, or MLflow).
• Demonstrated ability to transform research prototypes into maintainable, production-ready modules.
• Passion for testing, maintainability, and reproducibility as first-class ML engineering priorities.

Responsibilities

• Architect the next generation of Sunthetics’s optimization engine — enhancing reliability, modularity, and adaptability for new modeling features and experimental configurations.
• Implement experiment tracking and model versioning (e.g., MLflow, DVC, internal tracking systems).
• Build automated validation and testing frameworks for model inputs, outputs, and optimization routines using Pytest, Pydantic, and continuous integration tools.
• Collaborate with ML to productionize new Bayesian Optimization and Active Learning methods.
• Maintain connector layers between ML modules and the software platform (API-level integrations).
• Partner with MLOps and backend teams to improve deployment and inference pipelines, ensuring reproducible ML behavior across environments.
• Champion software engineering best practices — code modularity, version control hygiene, testing coverage, and CI/CD for ML.

Skills

Python

Pytest

Pydantic

Modular design

Strong Python engineering

Education

Bachelor’s or Master’s degree in Computer Science/Data Science/Applied Math

Tools

PyTorch

BoTorch

Optuna

MLflow

Job description

Sunthetics is seeking a Machine Learning Engineer (Infrastructure Focus) to strengthen and streamline our ML and Bayesian Optimization package development. You will build robust, production-ready workflows, improve testing and reproducibility, and collaborate with data science, MLOps, and software teams.

The role emphasizes test automation, model versioning, CI/CD for ML, and maintaining connector layers between ML modules and the platform, with a fully remote team.