Machine Learning Engineer — Scale to Millions | Remote & Equity

BKD

Columbia (SC)

Híbrido

USD 50.000 - 76.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Ventajas ofrecidas por este puesto de trabajo

Mentorship program
Equity

Descripción de la vacante

BKD in Columbia, SC is hiring a Machine Learning Engineer to scale our infrastructure for millions of users. The role offers a $50,000-$76,000 salary, with flexible remote options and mentorship—ideal for fast growth and impact in a hands-on environment.

You will migrate services to cloud-native tech, partner across teams remotely, and ensure backward compatibility while building robust tests and extracting insights from production systems.

Formación

  • At least 1 year of real-world ML experience.
  • 1 year of LightGBM práctica, plus a hunger for what's next.
  • Reliable, accountable, and able to follow through.
  • Practical regression analysis skills sharpened in a remote setting.

Responsabilidades

  • Migrate on-premise services to cloud-native architecture.
  • Collaborate with cross-functional partners to scope and deliver remote projects.
  • Engage with Columbia users to learn clustering needs.
  • Maintain backward-compatible clustering schemas.
  • Write regression-analysis integration tests to catch regressions before shipping.
  • Surface production data insights with data teams.
  • Tune MLOps queries to reduce timeouts on the SC database.
  • Decide when to buy XGBoost or build it for BKD's Columbia stack.

Conocimientos

Judgment
LightGBM práctica
Reliable
Regression Analysis
Communication discipline

Herramientas

XGBoost

Descripción del empleo

BKD in Columbia, SC is hiring a Machine Learning Engineer to scale our infrastructure for millions of users. The role offers a $50,000-$76,000 salary, with flexible remote options and mentorship—ideal for fast growth and impact in a hands-on environment.

You will migrate services to cloud-native tech, partner across teams remotely, and ensure backward compatibility while building robust tests and extracting insights from production systems.

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