Machine Learning Algorithm Engineer

SGS Consulting; Washington (District of Columbia); On-site; USD 120,000 - 170,000; Full time

Job summary

SGS Consulting in Washington, DC, seeks a proficient ML engineer to advance research-driven models across diverse applications. You will design, implement, and test ML models, and organize experiment results to guide future development.

You will work with teams to clean and prepare large datasets, debug software related to ML pipelines, and push performance and scalability improvements in production systems.

Qualifications

• Bachelor’s degree required; advanced degree (master’s or PhD) in a related field is a plus.
• Proven experience building and deploying machine learning models in production environments.
• Strong programming skills in object-oriented languages (C#/C++).

Responsibilities

• Develop and apply advanced methods, theories, and research techniques in machine learning algorithms.
• Design, implement, and test ML models for classification, regression, clustering, and pattern recognition tasks.
• Perform data engineering tasks: cleaning, processing, and organizing large datasets to support algorithm development and ML workflows.
• Organize, track, and document ML experiment results; analyze results to guide future model development efforts.
• Identify, troubleshoot, and resolve issues with software related to ML algorithms.
• Improve software performance and scalability in ML systems.

Skills

ML algorithms

C/C++

TensorFlow

PyTorch

scikit-learn

Experiment interpretation

Project management

Education

Bachelor's degree

Advanced degree preferred

Tools

TensorFlow

PyTorch

scikit-learn

Job description

SGS Consulting in Washington, DC, seeks a proficient ML engineer to advance research-driven models across diverse applications. You will design, implement, and test ML models, and organize experiment results to guide future development.

You will work with teams to clean and prepare large datasets, debug software related to ML pipelines, and push performance and scalability improvements in production systems.