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Burtch Works

Machine Learning Engineer

Burtch Works, Washington, District of Columbia, us, 20022

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Machine Learning Engineer

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Machine Learning Engineer

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Burtch Works This range is provided by Burtch Works. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range

$120,000.00/yr - $150,000.00/yr Job Title:

Machine Learning Engineer

Location:

Washington, D.C. (Hybrid - 2 days onsite)

About The Company

Our client is a global leader in AI-optimized scheduling and forecasting platforms, empowering and rewarding individuals in the fast-food and Quick Service Restaurant (QSR) industry through innovative solutions. The company fosters a dynamic startup environment, encouraging innovation, collaboration, and ownership.

Job Summary

The Machine Learning Engineer will design, train, deploy, and monitor machine learning models that address real-world customer needs. This role is central to scaling AI-powered scheduling and forecasting solutions. The position is based in Washington, DC, and reports to the Chief Analytics Officer.

Key Responsibilities

Build and test machine learning models to support their platform. Design, build, and deploy data and ML pipelines on AWS. Enable an iterative lifecycle for data products to improve, integrate, and deploy. Standardize workflows, analysis, and modeling for deployment and observability in production. Develop monitoring and observability systems for ML models and experiments. Collaborate across teams to align modeling with engineering standards.

Requirements

Education: Bachelor’s or Master’s degree in a quantitative field. Experience: 2–4 years of relevant experience. 4+ years’ experience with Python and ML frameworks. 1+ year of experience with MLOps and maintaining ML models at scale. Technical Skills: Strong knowledge and hands-on experience with: Python programming SQL and relational databases; ETL processes Cloud technologies (AWS, GCP, or Azure) Git or other version control systems Model versioning/tracking (DVC, MLFlow) ML pipeline development/deployment (Metaflow, Kubeflow, Prefect, Dagster) Containers (Docker, Kubernetes) Visualization and monitoring tools (Dash, Streamlit) Modeling/tuning/optimization with frameworks (sklearn, PyTorch)

Preferred Qualifications

Real-time inference deployment and monitoring (FastAPI, Ray Serve). CI/CD practices. Model deployment strategies (A/B testing, canary release). Cross-functional collaboration (DevOps, Data Engineering, Data Science). Time series analysis and predictive modeling.

Benefits

Salary range: $120-150K Health and Wellness: Industry-best benefits. Work-Life Balance: HYBRID – 2 days in office, 3 days from home.

Seniority level

Seniority level Mid-Senior level Employment type

Employment type Full-time Job function

Job function Engineering and Information Technology Industries IT Services and IT Consulting Referrals increase your chances of interviewing at Burtch Works by 2x Sign in to set job alerts for “Machine Learning Engineer” roles.

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