Interested in this AI/ML Engineer role at Keysight Technologies?
Apply Now →About This Role
Overview:
Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our \~16,800 employees create world\-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.
Our award\-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry\-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.
Responsibilities:
About the Role
AI infrastructure is being redefined in real time — new compute architectures, faster interconnects, new power and thermal demands, new validation challenges. Keysight sits at the center of that shift, and this Industry Marketing Manager role is part of a progression from marketing *at* the AI infrastructure industry to *leading* the conversation inside it.
This role owns how Keysight shows up in the AI infrastructure conversation: what we say, who we say it to, and how we connect what's happening in the industry back to real opportunities for our customers, partners, and business. You'll embody the understanding of what customers need in the areas of AI data centers, accelerated computing, high\-speed interconnects, networking, and power — and work with technical experts inside Keysight to turn that understanding into content, campaigns, and relationships that make Keysight easier to work with and harder to ignore.
This isn't a "just write about trends" role. It's a "help shape the industry and how Keysight shows up in it" role.
What You'll Do
- Read the industry, then act on it. Track what's shifting in AI compute, interconnect, networking, power, and data center infrastructure. Then translate what you find into concrete recommendations for messaging, campaigns, and where Keysight should be investing attention.
- Build Keysight's voice in the industry. Develop the core narrative, experiences, and assets conveying our AI infrastructure work — the kind that holds up with engineers and executives alike.
- Make Keysight easier to do business with. Create content and programs (white papers, articles, webinars, customer stories, videos, executive talks) that genuinely help customers and partners solve problems, not just content that promotes us.
- Show up where the industry gathers. Represent Keysight at key industry events, and build relationships with analysts, standards groups, and industry influencers that make us part of the conversation, not just an attendee.
- Work across teams. Partner with product marketing, portfolio, sales, field marketing, communications, creative, and regional teams to get campaigns into the world — and partner with subject\-matter experts, customers, and partners to keep the content credible and grounded.
- Know if it's working. Define what success looks like for your campaigns and content, track it, and adjust.
\#LI\-MO1
Qualifications: What You'll Need
- A technical foundation — a degree in electrical engineering, computer engineering, computer science, or a related field, or equivalent hands\-on experience.
- 5\+ years in industry marketing, product marketing, technical marketing, or similar B2B technology marketing work.
- Existing knowledge of AI infrastructure, data centers, accelerated computing, high\-speed interconnects, or power systems.
- A real ability to take something technically complex and explain it clearly — in writing, in a deck, out loud.
- Comfort learning fast in a technical space; you don't need to already be a networking or semiconductor expert, but you should be excited to become conversant quickly.
- Experience building marketing programs end\-to\-end: messaging, content, campaigns, and the teams needed to run them.
Nice to Have
- Background in electronic test and measurement, or AI data center validation.
- Existing relationships within the AI infrastructure ecosystem (analysts, standards bodies, industry groups).
The level of role will be based on applicable experience, education and skills; Most offers will be between the minimum and the midpoint of the Salary Range listed below.
California Pay range: MIN $126,000\.00 \- MAX $232,000\.00
Colorado pay range: MIN $117,000\.00 \- MAX $195,000\.00
District of Columbia pay range:MIN $117,000\.00 \- MAX $195,000\.00
Hawaii pay range: MIN $117,000\.00 \- MAX $195,000\.00
Illinois pay range: MIN $117,000\.00 \- MAX $195,000\.00
Maryland pay range: MIN $126,000\.00 \- MAX $211,000\.00
Massachusetts pay range: MIN $126,000\.00 \- MAX $211,000\.00
Minnesota pay range: MIN $117,000\.00 \- MAX $195,000\.00
New Jersey City pay range: MIN $126,000\.00 \- MAX $211,000\.00
New York pay range: MIN $139,000\.00 \- MAX $232,000\.00
Vermont pay range: MIN $117,000\.00 \- MAX $195,000\.00
Washington state pay range: MIN $126,000\.00 \- MAX $211,000\.00
Note: For other locations, pay ranges will vary by region.
This role is eligible for Keysight's Variable Pay Bonus Program
US Employees may be eligible for the following benefits:
- Medical, dental and vision
- Health Savings Account
- Health Care and Dependent Care Flexible Spending Accounts
- Life, Accident, Disability insurance
- Business Travel Accident and Business Travel Health
- 401(k) Plan
- Flexible Time Off, Paid Holidays
- Paid Family Leave
- Discounts, Perks
- Tuition Reimbursement
- Adoption Assistance
- ESPP (Employee Stock Purchase Plan)
- Restricted Stock Units
Careers Privacy Statement *\*\*\*Keysight is an Equal Opportunity Employer.\*\*\**
Keysight Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.
Salary Context
This $117K-$232K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Keysight Technologies, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($174K) sits 20% below the category median. Disclosed range: $117K to $232K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Keysight Technologies AI Hiring
Keysight Technologies has 3 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Santa Rosa, CA, US, Greensboro, NC, US, Colorado Springs, CO, US. Compensation range: $232K - $238K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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