Associate AI/ML Engineer
About The Position
In this role, you will develop and support machine learning and data-driven solutions that address business and operational challenges within enterprise platforms, including Palantir. You will collaborate with cross-functional teams to build scalable AI/ML workflows, contribute to Operational Database (ODB) 2.0 transformation initiatives and Metrics Ontology methodology work, and support the full machine learning lifecycle from data preparation through deployment and monitoring. You will analyze complex datasets, develop production-ready solutions, and apply best practices for data governance, security, and model validation.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field required.
- Understanding of machine learning concepts, including regression, classification, clustering, and model evaluation.
- Familiarity with software engineering fundamentals, including version control, testing, and debugging.
- Strong analytical, problem-solving, written, and verbal communication skills.
- Ability to work collaboratively in a team environment while managing multiple priorities.
Nice To Haves
- Relevant degree preferred.
- No prior experience required.
- Proficiency in Python and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch highly preferred.
- Working knowledge of SQL and experience with relational databases highly preferred.
- Exposure to cloud or data platforms such as AWS, Azure, or Palantir preferred.
Responsibilities
- Develop, test, and deploy machine learning models to support business and operational use cases.
- Build and maintain data pipelines to ingest, process, and transform structured and unstructured data.
- Perform exploratory data analysis to identify trends, patterns, and data quality issues.
- Write clean, efficient, and maintainable code for data processing and model development.
- Support end-to-end machine learning lifecycle activities, including data preparation, model evaluation, deployment, and performance monitoring.
- Develop workflows and integrate data sources within enterprise platforms, including Palantir.
- Collaborate with data engineers, analysts, and clients to translate business requirements into technical solutions.
- Document code, methodologies, and processes to support reproducibility and compliance standards.
- Apply best practices for data governance, security, and model validation.
- Troubleshoot and improve model and pipeline performance within production environments.
Benefits
- Comprehensive benefits plan
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
