Interested in this AI/ML Engineer role at Synopsys?
Apply Now →About This Role
Sunnyvale, California, United States
Category Product Management Hire Type Employee Job ID 18325 Base Salary Range $200000\-$300000 Date posted 08/06/2026
We Are:
At Synopsys, we drive the innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence, from self\-driving cars to learning machines. We lead in chip design, verification, and IP integration, empowering the creation of high\-performance silicon chips and software content. Join us to transform the future through continuous technological innovation. You Are:
You are a visionary and strategic leader, passionate about leveraging artificial intelligence to revolutionize the semiconductor and EDA industries. With over 15 years of expertise in product management and a robust background in electrical engineering, you thrive at the intersection of technology, business, and customer success. Your deep understanding of Generative AI \- spanning frameworks, foundation models, training and inferencing methodologies \- allows you to identify and capitalize on emerging trends that shape the future of design automation and chip development.
You excel in cross\-functional environments, adeptly influencing and collaborating with diverse teams to drive complex initiatives forward. Your leadership style is energetic, innovative, and empowering, inspiring others to achieve ambitious goals. With a track record of launching and scaling successful products, you are comfortable making data\-driven decisions, negotiating priorities, and presenting compelling business cases to executive stakeholders. You are recognized both inside and outside your organization as an expert and thought leader, and you are motivated by the opportunity to mentor, guide, and cultivate talent within your teams.
Your communication skills are exceptional, whether engaging with customers, partners, or internal teams, you craft clear, impactful messaging that drives understanding and action. You are equally passionate about financial performance, market expansion, and technical excellence, and you bring a holistic, customer\-centric approach to every challenge. Above all, you are driven by a desire to create products that deliver tangible value, shape industry standards, and enable the next generation of intelligent systems.
What You’ll Be Doing:* Defining and executing product and go\-to\-market strategy for Synopsys’ industry\-leading AI portfolio.
- Assimilating customer requirements, technology trends, and competitive intelligence to shape product roadmaps.
- Driving integrated marketing strategies encompassing thought leadership, demand generation, and customer\-focused campaigns.
- Developing and executing innovative go\-to\-market plans, including packaging, pricing, and new business models.
- Engaging directly with customers to understand requirements, anticipate market shifts, and identify future design trends.
- Building business cases for future development, negotiating product line priorities, and guiding technology roadmaps.
- Exploring inorganic growth opportunities such as M\&A and partnerships and supporting technology due diligence.
- Collaborating with cross\-functional stakeholders to foster ecosystem partnerships and drive product life cycle management.
- Owning messaging and positioning for digital implementation optimization and signoff timing analysis domains.
- Training, motivating, and guiding the sales force to advance the AI portfolio’s market presence.
- Developing and tracking the sales pipeline to meet financial targets and strategic objectives.
- Performing financial analysis and revenue forecasting to align business strategy and inform executive decisions.
- Serving as a recognized expert and role model in the field, representing Synopsys internally and externally.
The Impact You Will Have:* Shape the future of AI\-driven design automation and semiconductor innovation on a global scale.
- Drive the evolution and success of Synopsys’ AI portfolio, influencing industry standards and best practices.
- Accelerate customer outcomes by delivering cutting\-edge products that address real\-world challenges.
- Enhance Synopsys’ market share and financial performance through strategic product leadership.
- Foster a culture of collaboration, innovation, and continuous improvement across multi\-disciplinary teams.
- Establish Synopsys as a thought leader in AI for EDA and semiconductor industries.
- Enable rapid adoption of new AI technologies through compelling go\-to\-market strategies.
- Expand the company’s reach via strategic partnerships, acquisitions, and ecosystem development.
- Mentor and develop future leaders in product management and AI technology.
- Elevate customer satisfaction through tailored solutions and proactive engagement.
What You’ll Need:* 15\+ years of relevant experience in product management, ideally within EDA or semiconductor industries.
- Bachelor’s degree in electrical engineering (BS EE) or equivalent technical discipline.
- Expertise in Generative AI technologies, including frameworks, foundation models, training, and inferencing methodologies.
- Proven experience in one or more domains: Digital Design/Implementation, Verification, Signoff, Analog Design.
- Demonstrated ability to negotiate, influence, and lead in a matrixed organization.
- Successful track record in launching, managing, and growing technology products.
- Exceptional verbal and written communication and public speaking skills.
- Experience with financial analysis, revenue forecasting, and strategic planning.
- Understanding of go\-to\-market planning, packaging, pricing, and product lifecycle management.
Who You Are:* A strategic thinker with a passion for innovation and technology leadership.
- An energetic, inspiring leader who motivates teams to excel and embrace new challenges.
- Highly collaborative, with strong interpersonal skills and the ability to influence across functions.
- Customer\-centric, always seeking to deliver value and exceed expectations.
- Adaptable and resilient in fast\-paced, dynamic environments.
- Analytical and data\-driven, with a keen eye for market trends and business opportunities.
- Confident communicator and presenter, able to engage stakeholders at all levels.
The Team You’ll Be A Part Of:
You’ll join a forward\-thinking Product Management team at Synopsys, focused on driving innovation in AI and digital design technologies. The team is composed of talented professionals with deep domain expertise, a collaborative spirit, and a shared commitment to advancing the future of semiconductor and EDA solutions. Together, you’ll work cross\-functionally with engineering, marketing, sales, and executive leadership to deliver transformative products that redefine industry standards and empower customers worldwide. Rewards and Benefits:
We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non\-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.
At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.
In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job\-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.
Salary Context
This $200K-$300K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Synopsys, 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 $214,900 based on 6,420 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($250K) sits 16% above the category median. Disclosed range: $200K to $300K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Synopsys AI Hiring
Synopsys has 3 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Sunnyvale, CA, US, US. Compensation range: $300K - $349K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.