Machine Learning Engineer (Generative AI) (SANTA CLARA)

Machine Learning Engineer (Generative AI) (SANTA CLARA)

Santa Clara Full-Time 72000 - 88000 £ / year (est.) No working from home possible
Applied Materials

At a Glance

  • Tasks: Develop and innovate AI models for materials science and scientific discovery.
  • Company: Join a global leader in materials engineering solutions.
  • Benefits: Competitive salary, supportive culture, and opportunities for personal growth.
  • Other info: Collaborative team environment with excellent career advancement opportunities.
  • Why this job: Shape the future of technology with cutting-edge AI and machine learning.
  • Qualifications: MS or Ph.D. in relevant fields and strong machine learning skills.

The predicted salary is between 72000 - 88000 £ per year.

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.

What We Offer

  • Salary: $131,000.00 - $180,000.00
  • Location: Santa Clara, CA

You'll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company.

At Applied Materials, we care about the health and wellbeing of our employees. We're committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go.

TEAM OVERVIEW:

We are a passionate, cross-functional team at the forefront of applying cutting-edge AI and machine learning to accelerate scientific and materials innovation. Our mission is to create domain-specific, product-centric algorithmic solutions that drive real impact for our customers.

We thrive in a collaborative environment that encourages out-of-the-box thinking and values diverse perspectives. Here, creativity flourishes—groundbreaking ideas are born from the synergy of technical expertise and open-minded teamwork. We believe the best solutions emerge when everyone is empowered to share their unique insights and challenge conventional boundaries.

Our team leverages state-of-the-art generative AI and large language models to tackle complex problems in materials science, scientific discovery, and hardware design. We work closely with scientists, engineers, and product leaders to translate frontier research into practical, high-value applications.

Ideal candidates bring a strong research background, technical leadership, and a passion for learning new technologies. If you are excited to solve complex problems, drive innovation, and help shape the future of science with AI, join us on our journey to make possible a better future through intelligent discovery.

KEY RESPONSIBILITIES:

  • Develop, pretrain, fine-tune, and align LLMs and generative models tailored for scientific and materials science data, literature, and workflows.
  • Innovate post-training methods, alignment, and evaluation for domain-specific LLMs, ensuring models are robust, accurate, and trustworthy for scientific use cases.
  • Design and implement generative approaches to accelerate materials discovery, hypothesis generation, and hardware design.
  • Collaborate with scientists, engineers, and cross-functional teams to identify impactful applications of generative AI in materials science.
  • Build and curate scientific datasets, benchmarks, and evaluation protocols for model validation and continuous improvement.
  • Stay current with advances in AI, machine learning, and materials science, and publish original research in top venues.
  • Mentor junior team members and contribute to a collaborative, inclusive research culture.

TECHNICAL SKILLS:

  • Strong background in machine learning, deep learning, NLP, and generative AI, with a focus on scientific or technical domains.
  • Hands-on experience with LLM pretraining, supervised fine-tuning (SFT), post-training alignment (e.g., RLHF), and rigorous model evaluation.
  • Proficiency in Python and frameworks such as PyTorch or TensorFlow.
  • Experience working with structured and unstructured scientific data (e.g., literature, experimental results, simulation outputs) and developing domain-specific models.
  • Excellent communication skills, with the ability to collaborate across disciplines and present complex ideas to diverse audiences.

REQUIREMENTS/EDUCATION:

  • MS or Ph.D. degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics or related field.

Additional Information

  • Time Type: Full time
  • Employee Type: New College Grad
  • Travel: Yes, 10% of the Time
  • Relocation Eligible: Yes

The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.

Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, colour, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.

In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.

Machine Learning Engineer (Generative AI) (SANTA CLARA) employer: Applied Materials

Applied Materials is an exceptional employer that fosters a supportive work culture in Santa Clara, encouraging employees to learn and grow while tackling complex engineering challenges. With a commitment to employee wellbeing and professional development, we offer competitive salaries, comprehensive benefits, and opportunities for innovation in the cutting-edge field of materials engineering. Join us to be part of a team that not only drives technological advancements but also values your contributions and career progression.

Applied Materials

Contact Details:

Applied Materials Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Engineer (Generative AI) (SANTA CLARA)

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Applied Materials or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Applied Materials.

Tap into Online Developer Communities

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Explore Job Boards Specifically for Tech Roles

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We think you need these skills to ace Machine Learning Engineer (Generative AI) (SANTA CLARA)

Machine Learning
Deep Learning
Natural Language Processing (NLP)
Generative AI
Large Language Models (LLMs)
Python
PyTorch

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Applied Materials.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Applied Materials and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Applied Materials

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Applied Materials uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.