Sr Data Engineer-microsoft Fabric jobs at Kla in United States, Ann Arbor

Troubleshoot and refine optics modules and manufacturing processes for complex deep-UV imaging systems.Develop and maintain procedures, test fixtures, specifications, and train manufacturing, service, suppliers, and other engineer's on optics build, alignment and test processes.Solid understanding of Optics theory, especially imaging systems is a must.Experience with design software (CodeV, Zemax) and practical experience with statistical analysis is a plus.

Working on complex assignments where independent action and a high degree of initiative are required for problem solving.

Minimum Qualifications

Master's Level Degree and 0 years related work experience; Bachelor's Level Degree and related work experience of 2 years.

MS in Optical Science/Engineering, Electrical Engineering, Physics.

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Responsibilities

Work with functional groups to define requirement specifications needed to developelectrical/electronic

Responsible for technical project planning including project timelines, milestones, budget estimate and design reviews

Design mixed signal electronic systems, including schematic capture, simulation and layout review

Create test plans and perform testing, technical and root cause analysis to validate design performance at bench and system level including hands-on testing, spec validation, troubleshooting and root cause analysis

Qualifications

Minimum 5-7 year’s experience with BSEE, or 3-5 years experience with MSEE

Solid knowledge of electrical system design principles, analog/digital and mixed signal design, computer electronics, etc.

Strong technical project management skills and good understanding of engineering design phases and deliverables

Good track record to drive executions

Excellent problem-solving skills

Excellent written and verbal communications skills

Hands-on experience with lab equipment like logic analyzer, oscilloscope, soldering, etc.

Knowledge of board level FPGA/CPLD, motor/motion controls, power electronics, camera systems and image acquisition is a plus

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In this role, you’ll go beyondimplementation—you’llarchitect, optimize, and lead the development of advanced algorithms that push the boundaries of what’s possible in high-resolution imaging and real-time analysis. You’ll work closely with cross-functional teams to define technical direction, validate performance, and ensure seamless integration into production systems.

• Design and optimize cutting-edge algorithms for image processing, inverse problems, and computer vision
• Prototype in Python or MATLAB, and implement high-performance solutions in C++ on Linux
• Accelerate algorithm performance using CUDA/GPU programming
• Collaborate with systems, software, and hardware teams to translate complex requirements into scalable solutions
• Lead technical discussions, mentor junior engineers, and contribute to long-term algorithm strategy
• 5+ years of hands-on experience in image processing, computer vision, or machine learning in a production environment
• Deep expertise in spectral/spatial filtering, model-based methods, and inverse problem solving
• Strong proficiency in C++, with experience developing on Linux platforms
• Proven ability to prototype and validate algorithms in Python or MATLAB
• Familiarity with CUDA, TensorFlow, or other GPU-accelerated frameworks is a strong plus
• Experience architecting algorithms from the ground up and solving real-world vision challenges at scale

• Work on mission-critical technology that powers the semiconductor industry
• Be part of a high-caliber team where your expertise drives innovation
• Enjoy a hybrid work model with 3 days in the office and flexibility built in
• Grow your impact through technical leadership, cross-functional collaboration, and continuous learning

Minimum Qualifications

Doctorate (Academic) Degree and related work experience of 3 years; Master's Level Degree and related work experience of 6 years; Bachelor's Level Degree and related work experience of 8 years

or at +1-408-352-2808

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Responsibilities:

• Design electrical parts, modules, and subsystems that are part of a complete measurement system.
• Lead the entire design process, from requirement specifications and feasibility studies to cost and scheduling analysis.
• Conduct various analyses, including circuit, timing, thermal/cooling, and electrical loading.
• Perform thermal/cooling analysis and control.
• Program PLCs.
• Create conceptual and detailed designs using tools like AutoCAD, including detailed drawings and design review presentations.
• Procure prototype parts, test prototype assemblies, integrate into systems, and hand off to manufacturing.
• Develop supporting documentation, such as assembly instructions, test fixtures, procedures, and service manuals.
• Collaborate with other engineering groups, including mechanical, software, systems, and manufacturing, to ensure seamless integration and testing at both the subsystem and system levels.
• Partner with suppliers to ensure all design requirements are met and address product issues throughout the product lifecycle.

Qualifications:

• High-power design experience (>200V, >100A), with a strong preference for AC, but DC is acceptable.
• Experience with 3-phase circuit design (sources and loads).
• Proficiency in PLC programming (Siemens, Allen Bradley).
• Knowledge of communication protocols (e.g., Fieldbus, CAN).
• Understanding of controls, including thermal/cooling modeling, control and safety circuits, and PID tuning.
• Experience with MATLAB, Python, and LabVIEW.
• Strong understanding of AutoCAD (OrCAD or CREO is a plus).
• Hands-on diagnostic experience with complex electrical subsystems.
• Passion for working on groundbreaking technologies and excellent problem solving/analysis skills
• Excellent verbal and written communication skills.
• Expertise in Intrinsic Safety design is a plus!
• Travel up to 25%; ability to be flexible for domestic and international travel based on business needs.

Minimum Qualifications

Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years

or at +1-408-352-2808

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· Research emerging AI technologies focused on contextual classification, multimodal models, and AI databases
· Design, develop, and deploy proof of concepts from research
· Collaborate with cross-functional teams to integrate models into our existing systems and workflow
· Participate in AI research, systems architecture discussions and code reviews
· Conduct data engineering and analysis to improve model accuracy and efficiency
· Fine-tune models based on feedback and performance metrics

· Master’s degree and above in AI, Machine Learning, Computer Science, Engineering, or a related field.
· Proficiency in model fine-tuning techniques for large-scale models and tailoring them to specific tasks.
· Experience with inference optimization techniques (e.g. quantization, pruning, hardware-specific optimizations)
· Hands-on experience in machine learning, natural language processing, and AI technologies with contributions to open-source AI/ML projects.
· Strong programming skills in Python and familiarity with ML libraries (Ex. TensorFlow, Pytorch).
· Familiarity with MLOps practices and tools for deploying and managing models in production.
· Prior experience in a similar industry is a plus.
· Excellent problem-solving and analytical skills.
· Strong communication and teamwork abilities.

Minimum Qualifications

Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years

or at +1-408-352-2808

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Below is what you will be doing to drive improvements to our parts forecasting processes:

• Become a subject matter expert on our customer demand data environment:

• Understand the complexities and context around customer spare parts demand, situational factors such as customer contract entitlements, demand priority, product type, etc.

• Understand the associations of various parts and the respective products they belong to, which facilitates a mapping of where every unit in operation

• Identify problematic data records and anomalies that need to be resolved with data systems teams

• Build customer demand rate models to identify any variability across the fleet

• Identify any statically meaningful demand rate variation across customers, product types, customer entitlements, etc (and any combination thereof)

• Build bottoms up part forecasts across the fleet as a function of these customer demand rate models

• Work with demand frequency and volatility segmentation techniques to establish risk profiles for parts with unpredictable pattern

• Collaborate with other data scientists to input all the above data elements into various machine learning models designed to predict and optimize our customer experience

Preferred Qualifications:

• Manufacturing, Supply Chain, or related industry experience

Minimum Qualifications

• Bachelor’s degree with +5 years’ work experience, OR Master’s degree with +3 years’ work experience

• Educational background in Data Science, Data Analytics, IT or related field

• Strong data wrangling skills to extract and craft complex data into a usable format

• Strong skills with SQL, Python and/or R

• Experience with statistical / regression / ML modeling

• Ability to quickly learn new/differentlanguages/technologies/etc

• Communicate technical information to management and non-technical business partners

• Ability to collaborate closely with team members and cross functional domain experts to share knowledge and interconnect solutions

or at +1-408-352-2808

Job Scope and Complexity:

• Initially understand reliability models, then gradually own and run them to generate engineering insights

• Identify gaps between models and real-world scenarios, and develop innovative ideas to bridge these gaps with clever assumptions

• Write code as necessary to develop a fundamental understanding of reliability and statistical problems, and present insights and visualizations concisely

• Collaborate with cross-functional groups to obtain extensive data from the field and validate model results against field results

• Continuously drive innovation and features in the reliability, availability, and maintainability modeling domain

• Deliver written periodic reports to keep the wider team informed about status and progress

• Present ideas and results in concise decks and summary documents

• Lead cross-functional technical groups, convey key ideas, resolve differing viewpoints with a collaborative spirit, and move discussions forward

• Eager to learn and adept at picking up new technical concepts and software

• Be self-driven with a drive for problem-solving

Preferred Qualifications:

• Familiarity with any commercial reliability software (e.g., ReliaSoft)

• Demonstrated experience with part level and system level reliability analysis. Experience with reliability analysis of complex equipment systems a plus.

• Experience with failure mode analysis

• Familiarity with SQL and PBI

• Demonstrated experience using statistical and visualization packages for problem solving (e.g., JMP, Matlab, R, Python, PBI, Tableau, etc.). Familiarity with SQL is a plus.

• Master’s degree or doctorate in related discipline is preferred

• Experience in the framework of a Product Life Cycle and SEMI E10 definitions is a plus

Minimum Qualifications

• Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years

• Degree in mechanical engineering, electrical engineering, computer science engineering, statistics, or related engineering discipline

• Demonstrated experience of advancing solutions to technical problems in a cross-functional and multidisciplinary environment

• Evidence of learning new software and adaptability to continuously learn new technical topics

• Evidence of applying statistics in solving real world industrial problems. A strong understanding of statistical distributions and their applications in real world (e.g., Weibull, exponential, etc.)

• A strong grasp of basic probability concepts. An understanding of Bayes’ probability framework is considered a plus.

• Evidence of proficiency in coding to solve applied industrial problems

• Strong interpersonal and communication skills

or at +1-408-352-2808