Spotter - Remote Machine Learning Engineer

Client: Spotter

Contract: undefined

Job Description

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.

Responsibilities

• 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.

Requirements

• 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.

Additional 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.