Engineering Intern 1 - SG-Singapore (3301), Singapore
Originally posted 1 October 2026 by the employer.
About the role
This internship focuses on strengthening skills in Machine Learning (ML) models, with a focus on Bayesian surrogate / ML modeling and Bayesian Optimization (BO), by designing controlled synthetic test functions with tunable, domain-informed properties of the input-output response space.
What you'll do
- Design configurable synthetic test functions that generate input-output relationships with controlled properties.
- Use designed test functions to evaluate Bayesian surrogate modeling enhancements including customized GP kernel design.
- Explore data representation, dimensionality reduction, and latent space transformation approaches.
- Characterize BO-loop behavior across defined family of synthetic functions to identify performance regimes, failure modes, and gaps.
- Implement reusable synthetic test function components, experiment configurations, and evaluation of modeling and optimization pipelines in Python.
- Develop and benchmark Gaussian Process (GP) based surrogate models using predictive and uncertainty quantification metrics.
What you'll need
- Master or PhD students with strong interest and foundation in statistical machine learning, probabilistic modeling, experimental design, and Bayesian Optimization.
- Strong knowledge on Gaussian Processes, kernel methods, uncertainty quantification, and Bayesian Optimization.
- Strong Python programming and debugging skills.
- Ability to design controlled computational experiments, define meaningful metrics, and draw evidence-based conclusions.
Nice to have
- Experience with PyTorch, GPyTorch, BoTorch, NumPy, Pandas, and visualization libraries.
- Experience with synthetic benchmark functions, spatial data, structured outputs, and data transformation techniques.
Skills: Machine Learning models, Bayesian surrogate modeling, Bayesian Optimization, Gaussian Processes, Python
This role has been open 0 days — well below the 73-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
510
|
Median days open
73 d
|
Median salary
$225k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Lam Research | All employers we track in this specialty (510 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 2 | 510 |
| Open roles in the wider Software, Firmware & Systems family | 81 | 5930 · 145 employers |
| Median days open | 54 d | 73 d (−19 d vs this employer) |
| Median salary (USD postings) | — | $225k |
Skills observed across this category: Machine Learning models, Bayesian surrogate modeling, Bayesian Optimization, Gaussian Processes, Python
Who's hiring in this category
- Qualcomm · 106 open roles · median 106 d
- NVIDIA · 84 open roles · median 72 d
- AMD · 42 open roles · median 66 d
- Micron Technology · 31 open roles · median 56 d
- Mobileye · 20 open roles · median 69 d
- NXP Semiconductors · 15 open roles · median 59 d
How we counted: 510 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 2 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.