ML Engineer (Python, Docker, Git, ML libraries, CI/CD Pipelines) - 100% Remote

Overview

Remote
Depends on Experience
Full Time
No Travel Required

Skills

Bachelors Degree
Python
Docker
Git
ML libraries
CI/CD Pipelines
Monitoring
Testing Frameworks

Job Details

ML Engineer (Python, Docker, Git, ML libraries, CI/CD Pipelines) - 100% Remote

4+ years of experience

POSITION: ML Engineer (Python, Docker, Git, ML libraries, CI/CD Pipelines) - Remote
LOCATION: 100% Remote
DURATION: Full-Time Position Remote
SALARY: Excellent Compensation with benefits
SKILLS: Bachelor s Degree, Python, Docker, Git, ML libraries, CI/CD Pipelines, Monitoring, Testing Frameworks

DESCRIPTION:
We re seeking an Senior/Lead ML Engineer to play a pivotal role in advancing enterprise AI and intelligent data applications. This is a hands-on role that bridges machine learning, data engineering, and software development to deliver real-world impact. The ideal candidate thrives in fast-paced, high-standard engineering environments and is ready to step into a role with strong career growth opportunities, including senior engineering and technical leadership paths.

ROLE:

  • Lead platform upgrades to ensure products remain cutting-edge and effective.
  • Design and manage dynamic dashboards using a Python SDK, turning data into actionable visual insights for decision-making.
  • Optimize data pipelines and access patterns to improve performance and scalability.
  • Tackle runtime and performance challenges, ensuring reliability and responsiveness.
  • Architect robust, user-friendly, and scalable applications that account for current and future needs.
  • Collaborate closely with Product Managers to improve usability and deliver value to end users.

TECH STACK:

  • Python (primary language)
  • Docker, Git, ML libraries (pandas, numpy, scikit-learn, PyTorch)
  • CI/CD pipelines, monitoring, testing frameworks

REQUIREMENTS:

  • Bachelor s degree in Computer Science from a top university
  • Minimum of 4 years in Python software engineering, with proven focus on production ML deployment
  • ML Lifecycle Ownership: Demonstrated end-to-end experience model development - deployment - monitoring.
  • Strong production systems experience in rigorous engineering environments

PREFERRED EXPERIENCE:

  • Exposure to multiple programming languages and technologies beyond Python.

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