Solutions Engineering, Principal Engineer
Location
Mountain View, CA | United States
Job description
Job Description and Requirements
We are seeking a highly skilled and pioneering Generative AI Solutions Engineer to join our Gen-AI Center of Excellence (COE). As a Solutions Engineer, you will be responsible for innovating and contributing to the advancement of artificial intelligence in EDA. This work will greatly influence Synopsys’ customers with questions, like the following:
- How to use LLMs to improve hardware engineer efficiency?
- How to build a foundation model for EDA applications?
- How to architect generative AI solutions across a range of hardware design applications?
Duties - Architect Generative AI and Deep Learning applications for hardware design problems.
- Conduct experiments to evaluate model performance, identify areas for improvement, and implement optimizations.
- Collaborate with cross-functional teams to design and develop scalable solutions that meet business objectives.
- Participate in generative AI platform team to align with application requirements, deployment models and release timelines.
- Communicate complex technical concepts and findings to both technical and non-technical stakeholders.
- Lead solution architecture reviews, platform alignment and deployment models for generative AI applications.
- Drive innovation in new generative AI approaches and keep up to date on latest research in the field.
Minimum Qualifications - 1+ years of experience in applying machine learning and AI methods to engineering problems.
- This role requires a minimum of 2 years of experience working in hardware chip design or working in EDA/Cad tool development.
- Familiarity with python, and background in data structures and algorithms.
- Experience with LLMs, GPT models and other Generative AI techniques.
- Strong problem-solving skills and ability to work independently as well as collaboratively in a team environment.
- Excellent communication and presentation skills, with the ability to communicate complex technical concepts to both technical and non-technical stakeholders.
- Good understanding with hands-on experience in data cleansing and modeling for deep learning models in at least one domain (language, image, graphs, etc.)
- Experience with cloud-based machine learning platforms such as AWS, GCP, or Azure
Preferred Qualifications - MS or PhD in Engineering/Science with 10-12 years’ experience in computer science, Electrical Engineering, or related field.
- 2+ years of experience in applying machine learning and AI methods to engineering problems in hardware chip design or architecture.
- Strong understanding with hardware chip design and EDA methodologies, with demonstrable mastery of some aspect of the hardware design space.
- Understanding of deep learning architectures like Recurrent Neural Networks (RNNs), Graph Neural Networks (GNNs) and Convolutional Neural Networks (CNNs).
- Experience with deep learning frameworks like TensorFlow or PyTorch.
- Broad expertise and understanding of AI, NLP, LLM, and generative AI trends.
- Experience prototyping, experimenting, and testing with large datasets and training models.
The Engineering Excellence Group drives innovation velocity and enterprise infrastructure automation, which are critical elements of our growth and scaling strategy. This team is chartered to drive significant productivity, robustness, agility, and time-to-market advantage in the creation of Synopsys products and solutions. The group also leads corporate infrastructure transformation as we continue to drive IT operations leadership and invest in the next wave of disruptive technologies. The base salary range across the U.S. for this role is between $133,000.00 - $232,000.00. In addition, 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 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.
Inclusion and Diversity are important to us. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, military veteran status, or disability. #LI-PG1
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