Vision System Data Science Engineer (all genders)

Summary: Design and deploy computer vision algorithms and machine learning models to analyze large datasets for predictive analytics and process improvement. Lead the data science lifecycle, collaborate with engineering teams, and mentor junior staff to drive data-driven decisions in semiconductor manufacturing.

The impact you’ll make

Join Lam as a Data Scientist, where you'll design, develop, and program methods to analyze unstructured and diverse big data into actionable insights. You'll develop algorithms and automated processes to evaluate large data sets from disparate sources. Your expertise in generating, interpreting, and communicating actionable insights enables Lam to make informed and data-driven decisions.

What you’ll do

• Design, develop, and deploy computer vision algorithms for detection, classification, segmentation, anomaly detection, and predictive analytics.
• Build scalable machine learning and deep learning models using image, video, and multimodal sensor data.
• Lead the complete data science lifecycle, including data collection, labeling, feature engineering, model training, validation, deployment, and monitoring.
• Develop robust image-processing pipelines utilizing modern computer vision frameworks and cloud technologies.
• Collaborate with process engineers, software developers, hardware engineers, and product teams to deliver integrated vision solutions.
• Conduct root-cause analysis and use advanced analytics to improve yield, process stability, and equipment performance.
• Drive innovation by evaluating emerging AI, machine learning, and computer vision technologies.
• Mentor junior engineers and provide technical guidance on best practices in data science and machine learning.
• Translate analytical insights into standardized current best-known methods (cBKM) to enable scalable and sustainable business impact.
• Design, develop, and maintain production-grade Python applications, libraries, and data science solutions following established software engineering best practices.
• Process, structure, and analyze large-scale datasets while optimizing data pipelines, databases, and data architectures to support advanced analytics.
• Communicate complex analytical results and recommendations to technical and non-technical stakeholders, enabling data-informed decision-making.
• Contribute to the continuous advancement of data science, artificial intelligence, and Industry 4.0 initiatives within the organization.

Who we’re looking for

• Bachelor's or Master's degree in Data Science, Computer Science, Industrial Engineering, Applied Mathematics, or a related field.
• Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 3 years and a Master’s degree; or equivalent work experience.
• Proven experience developing, deploying, and managing predictive maintenance or machine learning models in production environments.
• Demonstrated ability to perform complex, non-routine engineering and data analyses that influence product and business decisions.
• Strong expertise in Docker and containerized application deployment.
• Project management skills, including the ability to translate strategic objectives into structured work packages and executable plans.
• Experience with large-scale data processing, data modeling, data warehousing, and data engineering concepts.
• Strong presentation and data visualization skills.
• Excellent verbal and written communication skills in English.

Preferred Qualifications

• Knowledge of optical systems, cameras, sensors, and imaging hardware.
• Expert-level proficiency in Python, statistical modeling, machine learning, and data visualization.
• Working knowledge of PowerShell, R, SQL, and database technologies.
• Experience developing and implementing artificial intelligence solutions and advanced analytics applications.
• Familiarity with cloud-based analytics platforms, MLOps practices, and software development lifecycle management.
• Experience leading data science projects in semiconductor environments.

What We're Offering

This position is subject to the [Austrian Collective Bargaining Agreement for Employees in the Metal Technology Industry](https://www.metalltechnischeindustrie.at/fileadmin/content/Dokumente/Kollektivvertrag/KV-2025_2026/FMTI_Mindesgehaltstabelle_2025.pdf) in occupation group F. The monthly salary is paid 14 times per year. Please follow the link below in the "Employment in Austria" section for further information.

Villach - a great place to live and work

Follow the link www.welcome2villach.at and you will find on the spot the most important information about living, working and studying in and around Villach/Austria

Our commitment

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 ("Lam" or the "Company") 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.*