Description

You will design and implement scalable machine learning solutions and data-driven workflows using Palantir platforms and AWS.

Responsibilities

• Leverage Palantir Foundry or Gotham for data integration, transformation, and advanced analytics.
• Design and implement scalable machine learning solutions using MLOps practices.
• Utilize AWS services including SageMaker, Lambda, EC2, S3, Redshift, Glue, and Kinesis.
• Develop and automate data pipelines using Python, SQL, and Bash.
• Troubleshoot and debug complex data systems to ensure reliability and performance.

Required Skills

• 15+ years of experience in data science, data engineering, or related domains.
• Hands-on expertise with Palantir Foundry and/or Palantir Gotham.
• Proficiency in Python, SQL, and Bash scripting.
• Experience with machine learning frameworks: TensorFlow, PyTorch, Scikit-learn, MLflow, and Kubeflow.
• Knowledge of AWS cloud-native workflows and services.
• Experience with containerization and orchestration using Docker and Kubernetes.
• Implementation of CI/CD pipelines using Jenkins, GitLab, or GitHub Actions.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, or a related field.

Preferred Skills

• Advanced degree (Master’s or Ph.D.) in a relevant field.
• AWS certifications such as Solutions Architect or Machine Learning Specialty.
• Experience with DevOps practices, real-time data streaming, and big data technologies like Hadoop, Spark, or Flink.

Key Skills

Education

Bachelor's or Master's degrees