As a Reliability Engineer, you work closely with design engineers to perform schematic design review and analysis through various design methods, such as simulation, to drive better NPI hardware quality and reliability.
Responsibilities
Perform schematic design review and analysis
Analyze specifications, datasheets, and application notes to create component device models
Support credit risk analytics activities across model development, independent validation, monitoring, and business reporting.
Conduct data extraction, reconciliation, quality checks, and analytical review using tools such as SQL, SAS, Python, Excel, and PowerPoint.
Translate analytical findings into clear insights and communicate results to model development, validation, business, and risk stakeholders.
Maintain clear documentation of analysis, validation observations, reporting logic, assumptions, and key findings.
Assist in the development and enhancement of IFRS 9 models, including PD, LGD, EAD, expected credit loss, and related risk estimation frameworks.
Requirements
Masters in Finance, Financial Engineering, Analytics or Mathematics, Computer Science, Statistics, Industrial Engineering, Operations research, or related field.
Masters in Mathematics/Statistics/Economics/Engineering or any other related discipline.
Support the development of AI/ML solutions for engineering drawing automation, document intelligence, and rule-based validation of 2D manufacturing drawings.
Responsibilities
Develop AI models for drawing analysis and validation
Build RAG-based knowledge retrieval solutions
Support model training using historical drawing datasets
Create proof-of-concept AI agents for engineering use cases
Work with CAD and PLM teams to understand engineering data structures
Requirements
Bachelor's degree in Computer Science, AI, Data Science, or related fields
Nice to have: Exposure to Engineering/CAD data
Nice to have: Knowledge of Manufacturing or Product Engineering processes
Nice to have: Experience with vector databases and on-premise AI deployments
Photonic Design Engineer within the Circuit Team to expand design, validation, and data analysis capabilities for PIC development and integrated photodetector projects.
Compensation
$120,000—$145,000 USD
$140,000—$164,000 USD
Responsibilities
PIC wafer-level data analysis and yield analysis
Integrated photonic component design and modeling
Circuit level simulation and layout
Packaged PIC validation and collaboration with cross-functional teams
Photodetector development including component design, test support and validation/qualification
Requirements
Ph.D.
M.S.
Nice to have: prior experience in integrated photodetector design and characterization
SoC Power Thermal Performance Validation and Optimization Engineer
Responsibilities
Develop and execute System-on-Chip (SoC)-level power, thermal, performance, and Power Management validation and optimization plans across Intel products.
Collaborate with architecture, design, firmware, and software teams to ensure power, thermal, performance, and Power Management meet competitive targets and specifications.
Establish and execute leakage, Dynamic Capacitance (Cdyn), Thermal Design Power (TDP), Digital Thermal Sensor (DTS), thermal protectors, Inverse Temperature Dependence (ITD), thermal margin, System-to-- Tester (S2T) correlation, data collection for the Electrical Critical Path (ECP), and Power Management methodologies.
Perform System-on-Chip (SoC)-level debug to identify root causes and resolve functional and triage failures related to power, thermal, Power Management, and performance.
Configure and set up data acquisition/loggers' equipment (e.g. Yokogawa) to collect and analyze power-thermal data.
Requirements
Bachelor's in Electronics, Electrical, Computer Engineering, or related field
Nice to have: Master's degree
Nice to have: hardware/software optimizations for power, thermal, performance
Nice to have: validation tools
Nice to have: lab equipment like Oscilloscope and Logic analyzer
Postdoctoral Researcher: Inverter-based Resources (IBR) Driven Power System Protection Study & Stability Analysis
National Laboratory of the Rockies · Posted Jul 13, 2026
Apply state‑of‑the‑art deep learning and computer vision techniques to curate high‑quality datasets and ground truth for autonomous vehicle perception, prediction, planning and control.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
Responsibilities
Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas.
Foster collaborative partnerships with researchers and engineers, transforming innovative research into robust, industrial‑strength machine learning models.
Take approaches from initial evaluation and experimentation all the way to shipping.
Define, collect, and curate training and evaluation datasets, focusing on scenario coverage and label quality.
Develop vision‑language models and embeddings for scenario search, classification, and automated data curation.
Requirements
PhD in Computer Science, Computer Engineering, or related field
MS in Computer Science, Computer Engineering, or related field
Reliability EngineerNewCisco · Bangalore, India
Photonic Design EngineerPsiQuantum · Remote