Remote Machine Learning Engineer

Posted 20 Hours Ago
Hiring Remotely in USA
Remote
Junior
Artificial Intelligence • Logistics • Software • Automation
The Role
Design, train, evaluate, deploy, and monitor machine learning models. Prepare and analyze large datasets, improve model performance through experiments, and collaborate with software engineers to integrate ML solutions into production while staying current with ML techniques.
Summary Generated by Built In

We're looking for a Machine Learning Engineer to help build and improve AI-powered products. You'll work with large datasets, train and evaluate machine learning models, and collaborate with software engineers to bring models into production.

This is a great opportunity for someone who enjoys solving practical problems with machine learning and wants to work on real-world AI applications.

What you'll do
  • Develop, train, and evaluate machine learning models.

  • Prepare and analyze datasets for model training.

  • Improve model performance through experimentation and testing.

  • Deploy and maintain ML models in production environments.

  • Collaborate with software engineers to integrate ML solutions into products.

  • Monitor model performance and continuously improve accuracy.

  • Stay up to date with new machine learning techniques and technologies.

What we're looking for
  • Basic understanding of machine learning concepts and algorithms.

  • Experience with Python.

  • Familiarity with machine learning libraries such as PyTorch, TensorFlow, or scikit-learn.

  • Comfortable working with data and writing clean, maintainable code.

  • Familiarity with Git.

  • Good problem-solving skills.

  • Strong written and verbal English communication.

Nice to have
  • Experience with large language models (LLMs).

  • Experience with cloud platforms such as AWS, GCP, or Azure.

  • Familiarity with SQL.

  • Experience deploying ML models.

  • Personal projects or open-source contributions related to AI or machine learning.

Requirements
  • 1+ year of experience in machine learning, software engineering, data science, or a related technical role or strong personal projects demonstrating ML skills.

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field is a plus, but not required.

  • Passion for learning and building AI solutions.

What we offer
  • Fully remote work.

  • Flexible working environment.

  • Opportunity to work on real AI products.

  • Challenging technical problems with room to grow.

  • Collaborative and fast-moving team.

  • Competitive compensation based on experience.

Skills Required

  • Basic understanding of machine learning concepts and algorithms.
  • Experience with Python.
  • Familiarity with machine learning libraries such as PyTorch, TensorFlow, or scikit-learn.
  • Comfortable working with data and writing clean, maintainable code.
  • Familiarity with Git.
  • Good problem-solving skills.
  • Strong written and verbal English communication.
  • 1+ year of experience in machine learning, software engineering, data science, or a related technical role OR strong personal projects demonstrating ML skills.
  • Passion for learning and building AI solutions.
  • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
  • Experience with large language models (LLMs).
  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • Familiarity with SQL.
  • Experience deploying ML models.
  • Personal projects or open-source contributions related to AI or machine learning.
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The Company
10 Employees
Year Founded: 2019

What We Do

Spotter.ai is an AI-powered freight technology company serving trucking carriers, fleet operators, and owner-operators across North America. Its integrated platform supports freight-market intelligence, recruiting, load optimization, transportation management, dispatch workflows, safety and compliance monitoring, and load-board automation. By combining real-time data with automation, Spotter.ai helps fleets improve operational visibility, reduce downtime, increase safety, and make more efficient, profitable decisions every day.

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