Data Scientist / 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