Research and Software Development Intern (AI)

Responsibilities:

• Reading and stress-testing recent papers against real-world problem constraints.
• Designing and running experiment ablations, benchmarks, failure-mode analysis, not just implementing a paper's happy path.
• Prototyping candidate architectures and defending design choices with evidence, not intuition.
• Turning validated experiments into documented, reproducible solution components.
• Writing technical rationale that holds up under review: what was tried, what failed, why the final approach won.

Ramp Plan:

• 30 days: Fluent in the problem space and existing experiment infrastructure. Running your first independent experiment.
• 60 days: Owning a research question end-to-end literature review through experiment through documented result.
• 90 days: Your experimental findings are shaping an actual architecture decision, not sitting in a notebook.

Requirements:

• Pre-final or final year, CS/AI/ML or related field.
• Strong Python fundamentals.
• Can read a paper critically and identify what's actually novel vs. incremental.
• Comfortable designing experiments, not just running them; knows what a fair ablation looks like.
• Comfortable with ambiguity and being wrong in public (research means most experiments don't work).

Nice-to-Have:

• PyTorch/transformers experience.
• Prior exposure to VLM, or self-supervised architectures.
• Open-source contributions or competition history.
• Interest in geospatial, sensor, or industrial time-series data.

Skills

ablation, ai, artificial intelligence, benchmarking, experiments, machine learning, ml, python