Machine Learning Engineer

Data Scientist / Machine Learning Engineer

(Mid–Senior Level)

12 month contract

Remote

Overview

We are looking for an experienced Data Scientist / Machine Learning Engineer to design, build, and deploy production-grade ML models while supporting the backend infrastructure required to run them at scale. This is a hands-on role combining applied machine learning, cloud engineering, and data pipeline development, with a strong focus on AI Content Moderation and Recommendation Engine systems.

Key Responsibilities

Take ownership of end-to-end ML production deployment, building and shipping new models largely from scratch, with responsibility for architecture, deployment pipelines, and operational reliability in collaboration with backend engineering.

• Design, train, deploy, and maintain machine learning models for production use, including AI Content Moderation and Recommendation Engine features
• Build and integrate backend infrastructure to support ML models and data pipelines
• Work with cloud-based systems to manage model training, deployment, and monitoring
• Improve data ingestion pipelines and feature engineering processes
• Develop scalable, reliable ML services in collaboration with backend engineering
• Collaborate closely with engineering and product teams to gather requirements and deliver solutions
• Communicate progress proactively and contribute to technical decision-making

Required Experience

• 3+ years of professional experience in Data Science, Machine Learning, or AI-related roles
• Strong Python proficiency for ML development and data processing
• Hands-on experience building and deploying ML models into production environments
• 2+ years of practical experience working with AWS infrastructure
• Solid background in Computer Science, Data Science, or a related technical discipline

Required Technical Skills

• Python (advanced)
• Production ML model development and training
• Experience building content moderation systems and/or recommendation engines
• AWS (deployment and infrastructure management), including:
• AWS Lambda
• AWS SQS
• AWS DynamoDB
• AWS Kinesis or Kafka
• Experience with at least one ML framework:
• PyTorch or TensorFlow