Principal Data Scientist, TPG
$145,000 - $360,000 USD yearly
Originally posted 15 September 2026 by the employer — open 3 days.
About the role
This role involves leading the architecture and delivery of AI systems within the Applied AI and Data Science organization, focusing on semiconductor engineering problems.
What you'll do
- Set the architecture and technical direction for applied AI, ML, and agentic AI work.
- Design end-to-end systems, including data pipelines, features, model development, evaluation, inference services, and monitoring.
- Build models for prediction, diagnosis, optimization, and decision support for semiconductor applications.
- Ship agentic AI for engineering analysis, knowledge retrieval, workflow automation, and decision support.
- Break challenges into roadmaps, turning points, and success criteria, reporting progress, risk, and model limits.
What you'll need
- Bachelor's degree in Computer Science, Data Science, Electrical/Computer Engineering, Statistics, Mathematics, Physics, or a related technical field.
- 8 years of relevant experience, or equivalent practical experience.
- Led complex AI, ML, data science, or software engineering programs as a technical lead.
- Hands-on machine learning and statistical modeling, including supervised learning, feature engineering, validation, performance evaluation, and reading model behavior.
- Python fluency with PyTorch, TensorFlow, scikit-learn, or XGBoost, with experience shipping models into production (inference pipelines, APIs, CI/CD, monitoring).
Nice to have
- Master's degree or PhD in Computer Science or a related technical field.
- People leadership: mentoring engineers, developing careers, and forming team capability.
- Experience in semiconductors, memory, storage, electronics, hardware systems, or advanced manufacturing.
- AI/ML deployed in cloud, hybrid, or on-prem environments: AWS, GCP, Azure, Kubernetes, OpenShift, or Docker.
- Experience with LLMs, RAG, and agentic workflows: agent frameworks, model gateways, knowledge graphs, enterprise search, MCP tool integration, or workflow orchestration.
Skills: applied AI, ML, agentic AI, data pipelines, model development, semiconductor applications
This role has been open 3 days — well below the 65-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
518
|
Median days open
65 d
|
Median salary
$229k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Micron Technology | All employers we track in this specialty (518 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 32 | 518 |
| Open roles in the wider Software, Firmware & Systems family | 258 | 5796 · 143 employers |
| Median days open | 37 d | 65 d (−28 d vs this employer) |
| Median salary (USD postings) | — | $229k |
Skills observed across this category: applied AI, ML, agentic AI, data pipelines, model development, semiconductor applications
Who's hiring in this category
- Qualcomm · 106 open roles · median 97 d
- NVIDIA · 85 open roles · median 65 d
- AMD · 43 open roles · median 60 d
- Micron Technology (this employer) · 32 open roles · median 37 d
- Mobileye · 25 open roles · median 51 d
- Analog Devices · 14 open roles · median 22 d
How we counted: 518 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 19 Sept 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.