Pay
In line with similar jobs
$125K–$272K against $166K–$240K, the middle half of what similar US postings state.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Senior Staff / Principal Machine Learning Scientist, AI Inference & Optimization
Santa Clara, California, United States
Open 4 months, first seen by us 120 days ago- Pay
USD 124,500–272,000/yearAnnual period assumed — pay source
Salary Range $124,500—$272,000 USD Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment. Netskope does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate.
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingAs a Senior Staff Machine Learning Scientist, you own the inference and optimization layer that makes AI in agentic workflows fast, efficient, and production-grade.
Fine-tune and evaluate models for bounded tasks, with eval harnesses that gate releases
Design and grow the task execution runtime for bounded sub-agents
Drive hardware acceleration, sparsity, and support for larger models
Partner with systems and backend engineers to ship and iterate on production signals
From the employer’s posting
As a Senior Staff Machine Learning Scientist, you own the inference and optimization layer that makes AI in agentic workflows fast, efficient, and production-grade. You fine-tune and evaluate models, push latency and throughput on real hardware, and build the runtime that executes bounded AI tasks, validated against usage from Netskope’s large customer base so you optimize where the data points, not where you guess.
Fine-tune and evaluate models for bounded tasks; build eval harnesses that gate a capability to release on real accuracy, latency, and security relevance.
Design and grow the task execution runtime (bounded sub-agents), pushing toward dynamic task generation and context compaction.
Drive hardware acceleration / sparsity and support for larger models as the platform matures.
Partner with the systems and backend engineers to ship capabilities end-to-end and iterate on real production signals.
Education & alternatives
Education - MS in Computer Science, Machine Learning, Electrical Engineering, or equivalent technical degree required, with a focus in AI/ML research; PhD in a related field strongly preferred. Compensation:
Posting record
Report an errorOpen 4 monthsWe first saw this posting 120 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 15, 2026120 days ago
- Recorded sightings
- 153
- Last seen by us
- Nov 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 120
Up longer than most. Similar jobs usually come down between day 8 and day 76.
At Netskope, jobs usually come down by about day 74.
From 5,323 similar postings that came down, and 5 of Netskope’s. Coming down is not always a hire.
Netskope is hiring
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring is picking up
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- C++
- Python
Where the posting names them
- Hands-on with fine-tuning (e.g. LoRA/QLoRA), quantization (GGUF/AWQ/GPTQ), and inference runtimes (vLLM/SGLang, TensorRT-LLM, ONNX Runtime, llama.cpp, or MLX/CoreML). On-device or edge inference experience is a strong plus. - Strong Python; comfort reaching into C++ for low-level interop is a plus. - Solid grasp of transformer internals and the levers that move real inference performance and cost: KV cache, attention, batching, memory footprint.
Your next step
Complete your application on www.netskope.com. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
About Netskope
- People
- About 3,281 in 2026.Annual report (SEC Form 10-K)
- Company
- Listed as NTSK.
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Join the Future of Security at Netskope
Netskope (NASDAQ: NTSK) is a leader in modern security and networking for the cloud and AI era. We secure and accelerate cloud, data, and AI in real time, everywhere. Thousands of customers, including more than 30 of the Fortune 100, trust the Netskope One platform, its Zero Trust Engine, and the powerful NewEdge network to gain full visibility and control without performance trade-offs.
At Netskope, our technology is driven by our greatest strength: our people. We believe that belonging powers innovation, and success is both personal and organizational. We embrace differences in gender, ethnicity, beliefs, ability, and identity, creating an environment where every voice is heard and respected. We empower our employees to bring their authentic selves to work, grow their careers through continuous education and mentorship, and lead with transparency and curiosity. Join a team where you belong, where you are encouraged to be an entrepreneur, and where together, we continue to redefine the landscape of security.
Visit Careers at Netskope to learn more. Follow us on LinkedIn and Instagram.
Positions are available at Senior Staff and above. Candidates are assessed individually and leveled according to their specific skills and background.
About the role
As a Senior Staff Machine Learning Scientist, you own the inference and optimization layer that makes AI in agentic workflows fast, efficient, and production-grade. You fine-tune and evaluate models, push latency and throughput on real hardware, and build the runtime that executes bounded AI tasks, validated against usage from Netskope’s large customer base so you optimize where the data points, not where you guess.
What’s in it for you
- High-impact ownership. You own the model layer of a net-new product that changes the performance and economics of agentic AI.
- Cutting-edge, unusual stack. The hard, interesting inference problems live here: quantization, KV-cache and memory management, sparsity, fine-tuning, and hardware acceleration under real-world resource constraints.
- Real scale to build against. Netskope’s customer footprint gives you production signals most teams never see, so you deploy, validate, and iterate fast.
What you will be doing
- Build and optimize the model inference path: quantization, KV-cache optimization, batching, and latency/memory/throughput tuning on constrained, commodity hardware.
- Fine-tune and evaluate models for bounded tasks; build eval harnesses that gate a capability to release on real accuracy, latency, and security relevance.
- Design and grow the task execution runtime (bounded sub-agents), pushing toward dynamic task generation and context compaction.
- Drive hardware acceleration / sparsity and support for larger models as the platform matures.
- Partner with the systems and backend engineers to ship capabilities end-to-end and iterate on real production signals.
Required skills and experience
- 10+ years of overall industry experience, with 4+ years hands-on in ML/AI (model development, fine-tuning, and inference optimization).
- Hands-on with fine-tuning (e.g. LoRA/QLoRA), quantization (GGUF/AWQ/GPTQ), and inference runtimes (vLLM/SGLang, TensorRT-LLM, ONNX Runtime, llama.cpp, or MLX/CoreML). On-device or edge inference experience is a strong plus.
- Strong Python; comfort reaching into C++ for low-level interop is a plus.
- Solid grasp of transformer internals and the levers that move real inference performance and cost: KV cache, attention, batching, memory footprint.
- Fluency with agentic coding systems and genuine curiosity about agent harnesses like Claude Code, Pi, and Codex, so you should already be building with them, or itching to.
- Clear communication: able to distill a model or infra bottleneck into an actionable concept for cross-functional teammates.
Education
- MS in Computer Science, Machine Learning, Electrical Engineering, or equivalent technical degree required, with a focus in AI/ML research; PhD in a related field strongly preferred.
Compensation:
At Netskope, salary is one component of our competitive total rewards package. The salary range for this position is as listed below. This is a national range. For purposes of complying with applicable laws, the range applies to candidates in California, Colorado, Illinois, Maryland, New York, Washington, and other states.
The successful candidate’s starting pay will also be determined based on job-related skills, experience, qualifications, location, and market conditions.
For all sales roles, the posted salary range is the On Target Earnings (OTE) range for the role, which is the sum of base salary and target commission amount at 100% goal achievement.
In addition to salary, candidates may be eligible for other forms of compensation such as participation in a bonus plan (for non-sales roles) and a stock award program. Candidates may also be eligible for a comprehensive health plan and other benefits that can be reviewed at Netskope Benefits site.
Salary Range
$124,500—$272,000 USD
Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment. Netskope does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate.
Netskope respects your privacy and is committed to protecting the personal information you share with us, please refer to Netskope's Privacy Policy for more details.
The application window for this position is expected to close within 50 days. You may apply by filling out the below information, or visiting our Netskope Careers site.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary Range $124,500—$272,000 USD Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment. Netskope does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate.
- Location & working pattern
Santa Clara, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.