Machine Learning Engineer

Infostrux Solutions

15h • Remote

About The Position

As a Machine Learning Engineer, you will help design, build, and deploy machine learning solutions that support real-world business needs. Working closely with senior engineers, data teams, and analysts, you will contribute to model development, data pipelines, and machine learning operations while gaining hands-on experience with modern cloud and data platforms. This role is ideal for someone who loves solving practical problems with machine learning, is eager to grow in machine learning operations, and thrives in collaborative, technical environments.

Requirements

• Strong foundation in machine learning fundamentals
• Proficiency in Python and common ML libraries (pandas, scikit-learn, PyTorch or TensorFlow)
• Experience in training and evaluating ML models
• Exposure to cloud platforms (AWS, Azure, or GCP)
• Familiarity with MLOps concepts such as model tracking, automated pipelines, and monitoring

Nice To Haves

• Basic understanding of containerization (Docker or Kubernetes)
• Experience working with APIs or production data workflows
• Interest in responsible AI, security, or governance

Responsibilities

• Build and train machine learning models based on project requirements, supporting model evaluation, validation, and performance improvements.
• Develop and maintain data preprocessing workflows and feature pipelines to ensure seamless data processing.
• Ensure data quality and consistency across ML systems.
• Contribute to ML deployment pipelines, model versioning, and monitoring.
• Collaborate with senior engineers on CI/CD and automation practices.
• Work with cloud platforms (AWS, Azure, GCP) and Snowflake to operationalize Machine Learning models.
• Integrate Machine Learning components with modern data architecture.
• Partner with data engineers, analysts, and senior ML engineers to translate business needs into technical solutions.
• Support documentation, testing, and reliability efforts.

Benefits

• 100% remote organization
• Work from home, as well as anywhere abroad where they are entitled to work for up to 3 months per year.
• Flexible schedule
• 4 weeks of vacation annually
• Paid personal and sick days
• Monthly bring-your-own-device allowance
• Professional development and industry-based certifications
• Time dedicated to work on non-client work and collaborate on new innovative ideas
• Co-working days and social events in main locations

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed