Machine Learning Engineer

Responsibilities

• Design, develop, train, optimize, and deploy machine learning models for real-world business use cases
• Translate business and product requirements into scalable ML and AI solutions
• Build and maintain machine learning pipelines including training, validation, deployment, and monitoring workflows
• Monitor model performance, data drift, and model decay to support retraining and optimization
• Develop and deploy ML models into production environments with high availability and scalability
• Collaborate with cross-functional teams including Data Scientists, Product Managers, and Software Engineers
• Optimize models for latency, throughput, and operational cost efficiency
• Apply Responsible AI principles including fairness, explainability, and governance

Requirements

• Bachelor’s degree in Computer Science, AI, Data Science, or a related field
• 3–7+ years of experience in Machine Learning or Applied AI
• Strong programming skills in Python, Java, or Scala
• Hands-on experience with TensorFlow, PyTorch, or Scikit-learn
• Experience deploying models using Docker or Kubernetes
• Knowledge of cloud platforms such as AWS, Azure, or GCP
• Experience with MLOps tools like MLflow, Kubeflow, or Airflow
• Familiarity with big data technologies including Spark, Kafka, or Databricks

Preferred Qualifications

• Background in NLP, Computer Vision, or Generative AI
• Experience building enterprise-scale AI or ML platforms
• Familiarity with Responsible AI and AI governance practices

About the Company

Master Works is seeking a highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems.