Staff Engineer - Machine Learning

Requirements

Education:

• Bachelor's or Master's degree in AI, Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or related field. AI major or strong research focus in degree strongly preferred.

Experience:

• Fresh graduate to 1 year. Work experience not required — demonstrated ML project competency is the primary criterion. Strong final-year project or thesis with a clear ML component; research internship preferred.

Must Have Skill:

• Python: Strong proficiency — clean, readable ML code; NumPy/Pandas basics
• PyTorch: Foundational — build, train, and evaluate a basic neural network independently from scratch
• CNN Architecture Basics: Understand and implement a basic image classifier; conceptual understanding of convolutional layers
• Surrogate Modeling Concepts: Why data-efficient ML matters in limited-data scientific settings
• Active Learning Awareness: Conceptual understanding of uncertainty-guided data selection
• MLflow Basics: Log experiments, parameters, and metrics for a training run
• Docker Basics: Write a Dockerfile to containerize a Python/ML application
• Model Evaluation: Standard metrics; produce a structured evaluation report
• Learning Mindset: Self-directed learning outside coursework; evidence of picking up new concepts quickly.

Good-to-Have Skill:

• U-Net or ViT exposure — academic project or course sufficient
• Uncertainty quantification basics — Monte Carlo dropout, ensemble methods
• Bayesian methods introduction — any probabilistic ML course or project
• Time-series or sensor data — any project with sequential or temporal data
• RL introduction — any RL course or gym environment experiment
• RAG basics, any LLM project
• AWS fundamentals; entry-level cloud ML deployment

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