Machine Learning Engineer – Neural Net Optimization
Job Description and Requirements
Looking for someone who has experience with Machine Learning, and is available to relocate to Sunnyvale, CA. Must be able to start between now and January 2024.
Synopsys’ Corporate Incubation Group is driving the incubation of bold new ideas that can result in big-step innovation, especially with cross business unit initiatives. In this entry level position, you will be developing AI technologies related to Neural Network Training by improving neural net training/optimization algorithms that are hooked into TensorFlow. We are looking for engineers who have a strong understanding of non-linear numerical optimization.
Duties
- Design and implement optimization algorithms for training neural networks.
- Debug and optimize neural networks for better performance.
- Conduct experiments to evaluate training performance, identify areas for improvement, and implement optimizations.
- Stay up to date with the latest research and advancements in the field of Deep Learning and apply this knowledge to improve our models and algorithms.
- Communicate complex technical concepts and findings to both technical and non-technical stakeholders.
- Participate in code reviews, testing, and deployment of learning models and algorithms.
Required Qualifications
- BS or MS degree in computer science, Electrical Engineering, Mathematics, or related field.
- Internships developing Machine Learning and AI technologies.
- Proven coding with C and Python on a Linux Platform.
- Excellent background in data structures and algorithms.
- Sound knowledge of deep learning architectures like Recurrent Neural Networks (RNNs), Long-Short-Term-Memory models (LSTMs), and Convolutional Neural Networks (CNNs).
- Experience with deep learning frameworks like Tensorflow or PyTorch.
- Familiarity with supervised and unsupervised learning algorithms like linear regression, logistic regression, random forests, gradient boosting, and k-means.
- Prior exposure to AI/ML workflows and tools.
- Experience prototyping, experimenting, and testing with large datasets and training models.
At Synopsys, we’re at the heart of the innovations that change the way we work and play. Self-driving cars. Artificial Intelligence. The cloud. 5G. The Internet of Things. These breakthroughs are ushering in the Era of Smart Everything. And we’re powering it all with the world’s most advanced technologies for chip design and software security. If you share our passion for innovation, we want to meet you.
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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.
The base salary range across the U.S. for this role is between $66,000 to $115,000. 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 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.