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- Tasks: Lead the design and implementation of advanced machine learning algorithms for cutting-edge metrology systems.
- Company: Join a leading tech company focused on innovation in semiconductor technology.
- Benefits: Enjoy flexible work options, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact by developing AI/ML solutions that drive performance and quality.
- Qualifications: PhD or MSc in relevant fields with extensive experience in data science and machine learning.
- Other info: Collaborative environment with a commitment to diversity and inclusion.
The predicted salary is between 48000 - 72000 £ per year.
The group you will be a part of works on the development of advanced systems for process diagnostics and metrology of semiconductor wafers. The group falls under CSBG (Customer Support Business Group) upgrades and metrology enabling our customers with premier customer support throughout their lifecycle with Lam. Along with R&D innovation, we drive performance, productivity, safety, and quality of customers installed base performance and deliver service and lifecycle solutions for their most critical equipment and processes.
We are seeking a seasoned and visionary data scientist to lead the design, development and implementation of advanced computer vision as well as machine learning/deep learning algorithms. Ideally a data scientist with a physics background, the candidate is expected to lead the development of Metior's equipment intelligence, AI/ML infrastructure, ensuring the creation of robust, scalable, and innovative solutions. The ideal candidate will combine deep technical expertise in data science and analytics with a strategic mindset to drive the development of cutting-edge AI/ML algorithms. This position requires understanding of the productization and deployment of ML solutions.
Responsibilities
- Design, Development and implementation of advanced machine learning algorithms as well as physics-based software solutions for our hybrid metrology systems including optical metrology solutions.
- Design and development of sophisticated algorithms for image segmentation and classification specific to our metrology systems.
- Provide strategic direction for the integration of advanced analytics, machine learning, and AI technologies.
- Select and evaluate data science tools, frameworks, and platforms to build a cohesive and efficient data science ecosystem.
- Hands On ML Model development and derive the right solutions for complex problems. Rapid prototyping and validation of new machine learning as well as deep learning algorithms.
- Work closely with software, system engineering and data-science teams to integrate algorithms into product systems as well as contributing to cross-functional innovations.
- Work with internal and external customers and stakeholders to define the requirements for next generation ML algorithm requirements to solve challenging customer problems.
- Data science related escalation management and troubleshooting potential issues from the field systems.
- Prepare presentations to all stakeholders and be able to host design reviews.
- Collaborate effectively with global development teams to ensure seamless deployment and continuous improvement. Stay abreast of emerging technologies to ensure the continuous evolution of our data science capabilities.
Who We’re Looking For
Technical Skills
- Extensive experience with data analytics, supervised and unsupervised machine learning including regression models, decision trees, feature engineering, frameworks like Pytorch, TensorFlow, SciKit-learn etc. Familiarity with MLOps with Databricks is a strong advantage.
- Strong background in optical physics, numerical simulations, advanced signal processing, computer vision and spectroscopy. Experience working with and handling huge datasets from advanced sensors and imaging systems.
- Proficiency in programming languages (e.g., Python, R) and familiarity with data science libraries and frameworks. Familiarity with C# is an added advantage.
- Ability to analyze large datasets and validate models for accuracy, robustness and reliability. Experience with ML deployment and monitoring strategies to track model performance over time and address issues proactively.
- Ability to work cross‑functionally and communicate complex modelling concepts to mixed engineering audiences. Curiosity-driven and a structured problem-solver.
- Background in parallel/distributed computing, profiling and optimization for computation and memory.
- Experience working in the development of semiconductor capital equipment systems is preferable.
Qualifications
- PhD or MSc in Physics, Applied Physics, Electrical Engineering, Optical Engineering or related field with strong modelling/analytical background.
- A minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience.
We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.
Lam Research is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.
Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. 'Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.
Data Scientist 4 in Bristol employer: Lam Research
Contact Detail:
Lam Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist 4 in Bristol
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with alumni from your university. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and computer vision. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. Get comfortable explaining your thought process and how you approach problem-solving. Remember, it’s not just about the right answer but how you get there!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist 4 in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with machine learning, computer vision, and any relevant projects that showcase your skills in data analytics and algorithm development.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background in physics and data science makes you the perfect fit for our team at StudySmarter.
Showcase Your Technical Skills: Don’t forget to list your technical skills clearly. Mention your proficiency in programming languages like Python and R, as well as your experience with frameworks like TensorFlow and Pytorch. We want to see what you can bring to the table!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and get you on our radar quickly!
How to prepare for a job interview at Lam Research
✨Know Your Algorithms
Make sure you brush up on your machine learning and deep learning algorithms. Be ready to discuss specific projects where you've implemented these techniques, especially in relation to computer vision and optical physics. This will show that you not only understand the theory but can apply it practically.
✨Showcase Your Problem-Solving Skills
Prepare to discuss complex problems you've solved in previous roles. Use the STAR method (Situation, Task, Action, Result) to structure your answers. Highlight how you approached challenges in data analysis or model deployment, particularly in a semiconductor context.
✨Familiarise Yourself with Tools
Get comfortable with the tools mentioned in the job description, like PyTorch, TensorFlow, and Databricks. If you have experience with MLOps, be ready to explain how you've used these tools to streamline processes or improve model performance.
✨Communicate Effectively
Since you'll be working cross-functionally, practice explaining complex concepts in simple terms. Think about how you would present your work to non-technical stakeholders. Clear communication can set you apart from other candidates who may struggle in this area.