Data Scientist / Machine Learning Engineer

Data Scientist / Machine Learning Engineer (Mid–Senior Level) 12 month contract RemoteOverview 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 onAI Content ModerationandRecommendation Enginesystems.

Key ResponsibilitiesTake 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, includingAI Content ModerationandRecommendation Enginefeatures 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-makingRequired 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 disciplineRequired Technical Skills Python (advanced) Production ML model development and training Experience buildingcontent 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