Local expert of eBeam(Defect Review SEM) Algorithm development and support group for Algorithm matters at customer site(Semiconductor & Display Industry)
Responsibilities
Develop state of the art algorithms in the fields of Deep Learning, Machine Learning, and Computer Vision.
Participate in Concept and Feasibility of new algorithmic features and their beta testing in customer site.
Deliver software specifications and production code to meet project milestones.
Algorithm integration in complex systems, including their HW and SW aspects.
Close cooperation with Algorithm and SW development groups in PDC & AMIND.
Requirements
MSc or above in exact sciences (Computer Science/Applied Math/Physics/Electrical Eng.)
Teach and develop curriculum for an Advanced Diploma in Artificial Intelligence, delivering lectures, tutorials, workshops, and practical sessions, while assessing student progress and maintaining academic records.
Responsibilities
Deliver lectures, tutorials, workshops and practical sessions related to Applied Artificial Intelligence
Teach students fundamental and advanced concepts in AI, machine learning and related technologies
Facilitate hands‑on learning activities, projects and case studies
Guide students in applying AI tools and technologies to solve real‑world problems
Provide academic support and consultation to students
Local expert of eBeam(Defect Review SEM) Algorithm development and support group for Algorithm matters at customer site (Semiconductor & Display Industry).
Responsibilities
Develop state of the art algorithms in the fields of Deep Learning, Machine Learning, and Computer Vision.
Participate in Concept and Feasibility of new algorithmic features and their beta testing in customer site.
Deliver software specifications and production code to meet project milestones.
Algorithm integration in complex systems, including their HW and SW aspects.
Assist application engineers with the troubleshooting of algorithm-related issues.
Requirements
MSc or above in exact sciences (Computer Science/Applied Math/Physics/Electrical Eng.)
Set the technical direction for how Qualified Health builds agentic AI systems across multiple product lines, defining shared architecture and engineering standards.
Compensation
The pay range for this role is between $250,000 and 310,000, depending on skills, qualifications, experience, and location. This role is also eligible for equity and benefits.
Responsibilities
Define the technical architecture and roadmap for agentic workflow infrastructure shared across multiple product lines.
Partner with engineering leadership on build-vs-buy and platform investment decisions.
Set engineering standards for LLM evaluation, deployment, safety, and monitoring across several teams, and help shape QH’s AI governance approach.
Act as a technical escalation point for high-ambiguity problems that cross product lines.
Mentor and develop Staff and Senior engineers and contribute to the applied AI career ladder.
Requirements
Bachelor’s degree in Computer Science, Engineering, or related field
Master’s degree in Computer Science, Engineering, or related field
Support development of AI-powered estimating tools, cost model development, and data collection, organization, and analysis, particularly working with unstructured data.
Compensation
Summary Pay Range: $97,750 - $132,250
Responsibilities
Work with Boeing data systems (IRE, EAS, PMAS, CSPR, etc.) to create databases and data tools, understanding how our different data sources connect to link them for various data tool solutions, managing the ETL process
Develop analytical solutions for imperfect datasets
Work with and understand datasets from a variety of programs/platforms and systems; Data normalization
Map data to common baselines to normalize and analyze cross platform data
Leverage Large Language Models (LLMs) to process and analyze text data
Requirements
Bachelor’s degree or higher in a quantitative field (e.g. statistics, operations research, information systems, bioinformatics, economics, computational biology, computer science, mathematics, physics, chemistry or similar quantitative fields)
As an ML engineer on our defense technology team, you’ll train, test, deploy, and maintain models that learn from data, contributing to the direction of mission-critical solutions by applying best-fit ML algorithms and technologies.
Compensation
The projected compensation range for this position is $55,200.00 to $126,000.00 (annualized USD).
Responsibilities
Train, test, deploy, and maintain ML models
Apply best-fit ML algorithms and technologies to mission-critical solutions
Collaborate with customers and other engineers to deliver world-class solutions
Requirements
Bachelor’s degree
Master’s degree in CS, Computer Engineering, Mathematics, Data Science, Software Engineering, Electrical Engineering, Physics, or a related field
Provide technical leadership in evaluating the performance and impact of advanced technologies, including precision agriculture, automation, autonomous systems, and digital products, while remaining hands-on in developing machine learning models, analytical solutions, and data pipelines.
Compensation
Competitive annual base salary ranging from $123,804 to $185,700, depending on qualifications and experience.
Responsibilities
Lead a sub-team of data scientists within the Technology Intelligence Proving Ground, establishing priorities, allocating responsibilities, and providing day-to-day technical guidance.
Define the technical strategy for evaluating the performance of machines, precision technologies, automation and autonomous capabilities, and digital products.
Design and conduct structured technology evaluations and benchmarks using repeatable methodologies, clear success criteria, and measurable outcomes.
Drive projects from initial concepts to tangible business results by framing problems, exploring data, developing prototypes, and delivering scalable solutions.
Independently develop machine learning models, analytical solutions, and data pipelines to assess real-world technology performance.
Requirements
Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Operations Research, or a related technical discipline
Advanced degree in statistics, mathematics, engineering, computer science, a quantitative discipline, or applied AI/ML (preferred)
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