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Cadence Machine Learning Jobs (NOW HIRING)

Cadence

Software Intern

San Jose, CA

$31.63 - $58.75/hr

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of ... Knowledge and experience with state-of-the-art machine learning technologies, parasitic modeling is ...

Sightly

Machine Learning Engineering Lead

$104K - $138K/yr

They are seeking a Machine Learning Engineering Lead to drive technical leadership in machine ... drift, retraining cadence, monitoring, cost management • Experience leading or mentoring ...

Cadence Design Systems Inc.

AI Engineer

San Jose, CA · On-site

$101K - $188K/yr

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of ... We use advanced math, computer science, graph theory and machine learning to solve the routing ...

GoodRx

Principal Machine Learning Engineer

$211K - $337K/yr

Leverage agentic AI to speed up development and deliver features on a consistent cadence * Drive ... machine learning systems at scale * Proven track record of leading and delivering large, complex ML ...

Cadence

Software Engineer II

San Jose, CA · On-site

$101K - $188K/yr

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of ... We use advanced math, computer science, graph theory and machine learning to solve challenging ...

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All JobsCadence Machine Learning Jobs

Cadence Machine Learning information

See salary details

$25.5K

$42.6K

$88K

How much do cadence machine learning jobs pay per year?

As of Jun 9, 2026, the average yearly pay for cadence machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are the typical collaboration dynamics between Cadence Machine Learning engineers and other teams within an organization?

Cadence Machine Learning engineers frequently collaborate with hardware design, software development, and product management teams to integrate machine learning models into electronic design automation (EDA) tools. This cross-functional teamwork ensures that ML solutions are both technically robust and aligned with customer needs. Regular communication, joint planning meetings, and shared project milestones help facilitate smooth integration and continuous improvement. Building strong relationships with these teams is key to successfully delivering machine learning features that enhance Cadence's product offerings.

What is a Cadence Machine Learning Engineer?

A Cadence Machine Learning Engineer is a professional who specializes in applying machine learning techniques and algorithms within Cadence Design Systems' suite of electronic design automation (EDA) tools. Their role typically involves developing, implementing, and optimizing machine learning models to improve processes such as chip design, verification, and testing. They work closely with hardware engineers and data scientists to automate tasks, enhance design accuracy, and increase efficiency in semiconductor development. This position requires a strong background in both machine learning and electronic design automation.

What are the key skills and qualifications needed to thrive as a Cadence Machine Learning Engineer, and why are they important?

To thrive as a Cadence Machine Learning Engineer, you need a solid background in machine learning algorithms, data analysis, and programming, typically supported by a degree in computer science, engineering, or a related field. Proficiency with Cadence EDA tools, Python, TensorFlow or PyTorch, and familiarity with hardware design and verification systems are commonly required. Exceptional problem-solving, communication, and teamwork skills help you translate complex ML models into practical solutions for electronic design automation. These abilities are crucial for developing innovative, efficient workflows that accelerate chip design and verification processes.

What is the difference between Cadence Machine Learning vs Cadence Data Scientist?

AspectCadence Machine LearningCadence Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegree in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentTech companies, R&D labs, product teams focusing on ML modelsBusiness analytics, data analysis, and model development in various industries
Employer & Industry UsageTechnology firms, semiconductor industry, embedded systemsFinance, healthcare, marketing, and tech sectors

Cadence Machine Learning specialists focus on developing and deploying ML models within embedded and hardware environments, often in tech and semiconductor industries. In contrast, Cadence Data Scientists analyze data to inform business decisions across various sectors. Both roles require strong analytical skills but differ in their focus on ML model development versus data analysis.

More about Cadence Machine Learning jobs
What states have the most Cadence Machine Learning jobs? States with the most job openings for Cadence Machine Learning jobs include:
What job categories do people searching Cadence Machine Learning jobs look for? The top searched job categories for Cadence Machine Learning jobs are:
Cadence Machine Learning jobs near you
Infographic showing various Cadence Machine Learning job openings in the United States as of May 2026, with employment types broken down into 2% Internship, 87% Full Time, 3% Temporary, 6% Contract, and 2% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Scientific Software Developer II - Modeler

OpenEye, Cadence Molecular Sciences

Santa Fe, NM • On-site

Full-time

Posted 6 days ago

Job description

Job Summary:
OpenEye, Cadence Molecular Sciences is an industry leader in computational molecular design and is seeking a Scientific Software Developer II – Modeler to join their team. The role involves developing scalable workflows for drug discovery using OpenEye's Orion platform, focusing on molecular modeling and advanced simulation techniques.
Responsibilities:
• Develop highly scalable and integrated workflows for relative binding free energy workflows in lead optimization
• Explore machine learning models such as 3D-QSAR using large-scale relative binding free energy calculations
• Develop data-driven models using 2D cheminformatics and 3D molecular shape representations
• Work on retrospective and prospective projects both internally and with collaborators to validate methodologies.
• Work with Orion project team to further optimize compound design workflows in Orion.
Qualifications:
Required:
• PhD (or equivalent experience) in computational chemistry, chemistry, or related field with 0 – 5 years relevant experience
• Knowledge of molecular dynamics simulations, binding free energy calculations, protein-ligand interactions, or machine learning
• Experience in designing hypothesis-driven computational experiments, and data-driven decision making
• Programming expertise, ideally in Python, preferably with experience using AI coding agents
• Experience in or desire to learn about the pharmaceutical industry
• Strong desire to learn about customer problems and find practical solutions
• Demonstrated ability to work both as part of a team and independently
Preferred:
• Experience with OpenEye software/toolkits
• Expertise with traditional machine learning and modern deep learning methods
• Experience with synthetically accessible, pharmaceutically relevant generative chemistry
Company:
OpenEye, Cadence Molecular Sciences is an industry leader in computational molecular design based on decades of delivering rapid, robust, and scalable software, toolkits, and technology and design services across the drug discovery process. Founded in 1997, the company is headquartered in Santa Fe, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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