Internship Opportunity

Scientific Dataset Engineering & ML Infrastructure

Location: Bengaluru, India

Duration: 3–6 months

Target: B.Tech, M.Tech, BS-MS, PhD students

What you will do :

• Implement geometry analysis, numerical computations, deduplication. Optimize for 500k+ cases.
• Quality Control & Validation: Design solution quality metrics, develop anomaly detection, build automated audit pipelines. Test edge cases thoroughly.
• Data Generation & Curation: Orchestrate parametric simulation variants, integrate with solvers, implement diversity-aware deduplication.

Requirements

Must Have:

Essential:

•       B.Tech/M.Tech (final year) or PhD in Engineering, or Applied Math

•       Strong numerical methods knowledge (FEM, FVM, FDM, convergence analysis)

•       Hands-on coding: Python (NumPy, SciPy, Pandas), scientific computing experience

•       Comfort with real solvers and scientific workflows (not just ML frameworks)

Highly Valued:

•       C++ expertise (C++17+), memory optimization, performance tuning

•       GPU computing (CUDA) or HPC experience (OpenMP, MPI)

•       Hands-on with scientific solvers

•       Published papers or significant open-source contributions

FAQ

Q: What domain is this?

A: Confidential. Disclosed after NDA signing.

Q: Do I need domain expertise?

A: Strong numerics and coding required. Domain knowledge is learnt.

Q: Mentorship level?

A: Weekly 1:1s, daily Slack, code reviews on every PR, open office collaboration.

Q: Remote work possible?

A: No.

Q: Will this lead to a full-time offer?

A: Full-time offers considered for proven track records in execution and code quality. Top performers (~15-20%) fast-tracked for R&D/SDE roles. Strong recommendations provided to all.

Benefits

Why This Internship Is Valuable

1.Access to Advanced Infrastructure & Research Support

2.Ownership & Visibility

3.Exceptional Mentorship & Learning Curve

4.Builds a profile aligned with industry research roles.

5.Real Research-Grade, Production-Impact Work