Role overview
- Design and develop AI capable of performing in uncertain and dynamic or unstructured real-world scenarios
- Design, build, train, and optimize machine learning models (supervised, unsupervised, and/or deep learning)
- Develop end-to-end ML pipelines, from data ingestion and feature engineering to model evaluation and deployment
- Deploy models into production environments and monitor performance, drift, and reliability
- Work with structured and unstructured data from multiple sources
- Collaborate with software engineers to integrate ML models into applications, APIs, or platforms
- Partner with stakeholders to translate business needs into ML-driven solutions
- Evaluate model performance using appropriate metrics
- Tune models for accuracy, efficiency, scalability, and interpretability
- Implement versioning, testing, and documentation for ML assets
- Follow secure coding practices and data privacy standards
- Document models, assumptions, and limitations clearly
- Contribute to ML best practices, standards, and reusable components
Basic qualifications
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field (or equivalent experience)
- Strong proficiency in Python and common ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience working with data pipelines, APIs, and cloud-based environments
- Understanding of core ML concepts, including model training, validation, and deployment
- Experience with SQL and data manipulation tools
- Experience with containerization (Docker, Kubernetes)
- Familiarity with data visualization tools
Preferred qualifications
- Doctorate or Master’s degree in a relevant field
- Experience deploying ML models in production environments
- Familiarity with MLOps tools and practices (CI/CD, monitoring, model lifecycle management)
- Experience with cloud platforms and modern compute
- Knowledge of NLP, computer vision, or large language models (LLMs)
- Experience with agent, agentic and cognitive AI
- Prior experience supporting government, defense, or enterprise customers
- Experience working in regulated or compliance-driven environments
Tags & focus areas
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