Lead Automative Use Cases Validation Engineer Job at AMD (Bangalore)

Senior Engineer / Lead Engineer - Virtual Engineering - AI ML

Sponsorship:  GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE....

Location

India , Bengaluru

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Bachelor's or Masters Degree Mechanical/Automobile/Production /Mechatronics Engineering discipline or similar
5+ years in Automotive Manufacturing / Manufacturing Engineering Experience
1+ year experience in implementing AI/ML solutions in Automotive use cases
Should have executed at least 2 end-to-end projects in the text or Image data domain (from problem definition to deployment)
Strong programming skills in Python
Proficiency with ML/DL frameworks like Scikit-learn, TensorFlow, PyTorch, XGBoost
Solid understanding of statistics, probability, and linear algebra
Experience in data preprocessing, feature engineering, ETL and Exploratory Data Analysis (EDA)
Experience with MLOps platforms (MLflow, Kubeflow, Vertex AI, Azure ML)
Knowledge of ML model evaluation

Job Responsibility

Collaborate with stakeholders to understand business problems in the in the Manufacturing Engineering and Operations space and solve them using ML methodologies
Design, develop, and fine-tune AI/ML models for classification, regression, clustering, and recommendation systems
Work with MLOps tools to automate workflows, CI/CD pipelines, and model monitoring
Evaluate, validate, and benchmark model performance using appropriate metrics
Deploy AI models into production environments in collaboration with IT/AI teams
Establish monitoring and maintenance processes to ensure model accuracy over time
Ensure that all AI solutions comply with organizational data security, confidentiality, and regulatory requirements
Document workflows, results, and lessons learned for organizational knowledge sharing
Stay updated on advancements in ML model evaluation, ML frameworks, end-to-end ML pipelines

Fulltime

Senior Engineer / Lead Engineer - Virtual Engineering - AI CAE

Senior Engineer / Lead Engineer – AI CAE will Drive AI innovation in CAE analysi...

Location

India , Bengaluru

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Bachelor's or Masters Degree Mechanical/Automobile/Production /Mechatronics Engineering discipline or similar.
5+ years experience in CAE at Automotive Product Development / Manufacturing Engineering.
3+ years' experience in implementing AI solutions in CAE
Should have executed at least 5+ years of Core CAE domain (from problem definition to deployment) experience.
Strong programming skills in Python, MATLAB, CAE tool-specific APIs (Altair suite, NASTRAN, ANSYS APDL, Abaqus etc.), workflow automation.
Experience with ML frameworks like Pytorch, TensorFlow.
Understanding of data annotation tools and MLOps workflows.
Experience in data handling and feature engineering.
Strong problem-solving and analytical mindset.
Experience in domain-specific AI use cases (manufacturing, automotive, etc.).

Job Responsibility

Collaborate with stakeholders to understand business problems in the CAE domain and translate them into AI solutions.
Design, develop, and fine-tune AI/ML models for Simulation result prediction and design optimization, Automating repetitive CAE tasks (meshing, boundary conditions, post-processing).
Evaluate, validate, and benchmark model performance using appropriate metrics.
Deploy AI models into production environments in collaboration with IT/AI teams.
Establish monitoring and maintenance processes to ensure model accuracy over time.
Ensure that all AI solutions comply with organizational data security, confidentiality, and regulatory requirements.
Document workflows, results, and lessons learned for organisational knowledge sharing.
Stay updated on advancements in neural networks, multi-physics simulations, surrogate modelling and physics-informed learning techniques.

Fulltime

Senior Engineer / Lead Engineer - Virtual Engineering - AI CFD

Senior Engineer / Lead Engineer – AI CFD will Drive AI innovation in CFD domain....

Location

India , Bengaluru

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Bachelor’s or Masters Degree Mechanical/Automobile/Production /Mechatronics Engineering discipline or similar
5+ years experience in CFD at Automotive Product Development / Manufacturing Engineering
2+ years experience in implementing AI solutions in CFD
Should have executed at least 5+ years of Core CFD domain (from problem definition to deployment) experience
Strong programming skills in Python and C++ for automation and solver integration
Experience with ML frameworks like Pytorch, TensorFlow
Knowledge of surrogate modeling, reduced-order modeling (ROMs), and regression techniques
Experience in data handling (large-scale CFD datasets) and feature engineering(feature extraction from flow fields like velocity, pressure, turbulence quantities)
Strong problem-solving and analytical mindset
Understanding of data annotation tools and MLOps workflows

Job Responsibility

Collaborate with stakeholders to understand business challenges in the CFD space and solve them using API based customization and AI methodologies
Collect, clean, annotate, and prepare datasets for text analysis and image comparison tasks
Design, develop, and fine-tune AI/ML models for: Automating mesh generation, solver setup, and post-processing of CFD results
Building optimization pipelines for thermal and fluid systems using AI-assisted approaches
Evaluate, validate, and benchmark model performance using appropriate metrics
Deploy AI models into production environments in collaboration with IT/AI teams
Establish monitoring and maintenance processes to ensure model accuracy over time
Ensure that all AI solutions comply with organizational data security, confidentiality, and regulatory requirements
Document workflows, results, and lessons learned for organizational knowledge sharing
Stay updated on advancements in neural networks, multi-physics simulations, surrogate modelling and physics-informed learning techniques

Fulltime

Lead Engineer - Robotic Simulation

Job Description Sponsorship:  GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSH...

Location

India , Bengaluru

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Master’s or Bachelor’s degree in Mechanical/Production/Automobile or equivalent Engineering discipline
4 to 12 years of experience in Robotics from Automotive OEMs / Engineering Organizations
Strong knowledge of robotic systems, manufacturing automation, and Shop driven processes
Strong understanding of robotic simulation, offline programming, and virtual validation methods
Knowledge of robot applications such as welding, material handling, dispensing, roller hemming, laser welding, and clinching
Knowledge of controls integration, robot interfaces, tooling, and manufacturing equipment validation
Understanding of project management principles including scope, timing, risk, issue tracking, and resource planning
Knowledge of GM engineering standards, templates, e-tools, and standardized work practices
Awareness of emerging technologies in robotics and immersive solutions including VR, AR, and MR
Ability to develop conceptual solutions and translate them into executable robotic applications

Job Responsibility

Identify opportunities for new robotic applications across manufacturing shops
Build conceptual engineering solutions for robot-based deployment applications
Perform robotic simulation and support on-floor execution for deployment projects
Oversee robot configuration and application across processes including welding, material handling, dispensing, and other manufacturing operations
Select the most suitable robot model based on process requirements, payload, and cycle time targets
Coordinate with process suppliers for special applications such as roller hemming, laser welding, clinching, and other advanced manufacturing processes
Work with stakeholders to develop in-house engineering solutions for a wide range of robot applications, including collaborative robots
Recommend and implement improvements that reduce shop-floor execution time and improve overall project efficiency
Contribute to the development and maintenance of engineering standards, templates, e-tools, and best practices
Drive deployment of standard methods and tools across new projects

Fulltime

Model Risk and Validation Lead

The Model Risk & Validation Manager will be responsible for the risk measurement...

Location

Ireland , Dublin

Salary:

Not provided

Soc Debug Tools Validation Engineer

WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great prod...

Location

India , Bangalore

Salary:

Not provided

AMD

Expiration Date

Until further notice

Requirements

MS / M Tech / BE/ in Electronics and Communication/Computer Engineering
Should have total relevant work experience of minimum 6+ years
Product development/validation or systems engineering background with hardware platforms and their software & firmware ecosystems
Familiarity with x86 Debug Tools ,DFT (Design for Testability)
Good understanding of DFT /JTAG 1149.x / BMC (Baseboard management controller)
Experience in any test automation tools
Familiarity with Windows and Linux
Excellent trouble shooting and debugging techniques with attention to detail
Experience with standard automation and scripting (Shell programming/Ruby/Perl/Python)
Knowledge on test tools (Coverage tools / Security testing tools / Performance / API testing and stress testing techniques)

Job Responsibility

Own the multi-functional validation of AMD Silicon Debug Tools products
Ability to create Test strategy, Test plan and Test execution
Work under minimal supervision
Lead Quality assurance tasks and enhance product quality
Work across engineering teams and subject areas spanning silicon, firmware, hardware, and software
Coordinate debug of issues and drive them to closure
Pull together meetings, set up clear agendas and follow up on action items
Deliver regular progress updates toward program goals
Make tough decisions such as priority calls based on partial or incomplete data
Proactively drive continuous improvement for Debug Tools and performance activities

Fulltime

Robotics Verification & Validation Engineer

We are seeking a detail-oriented and rigorous V&V (Verification & Validation) en...

Location

United States , Burlingame

Salary:

208000.00 - 289000.00 USD / Year

Senior AI/ML Validation Engineer

We are seeking an experienced and versatile professional with expertise in valid...

Location

India , Hyderabad

Salary:

Not provided

AMD

Expiration Date

Until further notice

Requirements

8–12 years in QA/Test for systems software or platform engineering, with at least 4 years focused on GPU software, device drivers, or firmware validation
Demonstrable ownership of validation for AI/ML pipelines and serving stacks using PyTorch and at least one modern inference framework (e.g., vLLM), including accuracy baselining and performance regression detection
Proven expertise testing drivers and firmware with hands-on work in: PCIe fundamentals (link training, BARs, MSI/MSI-X), DMA engines, interrupt handling, and memory models
Failure modes: error injection, recovery paths, power/thermal events, and persistence across reboot/upgrade cycles
Deep proficiency in Linux (kernel/user space) and practical experience with Windows driver ecosystems
ability to: Read kernel logs and symbols, trace with ftrace/perf/ETW, and perform cross-layer debugging
Build custom kernels/modules and analyze crash dumps (kdump, WinDbg)
Strong programming for test automation: Python for framework and orchestration (pytest or equivalent), robust mocking/fixtures, and data-driven test generation
C/C++ for low-level test harnesses, protocol exercisers, and performance micro-benchmarks
Bash/PowerShell for environment setup, CI scripting, and reproducibility

Job Responsibility

Own end-to-end test strategy for AI/ML workflows (PyTorch, vLLM), GPU runtimes, drivers, and firmware across kernel and user space
Develop scalable automation frameworks spanning unit, integration, HIL (hardware-in-the-loop), system, and end-to-end tests
Implement and maintain CI quality gates (GitHub Actions/Workflows, Jenkins), including automated build, test execution, artifact management, reporting, and flake reduction
Design and execute performance, stress, reliability, soak, and long-haul tests targeting GPU compute, memory, I/O, and serving throughput/latency
Validate cross-platform compatibility (Linux/Windows), covering driver interfaces, kernel interactions, firmware behavior, and runtime stability
Create reproducible environments with containers/orchestration
instrument telemetry and observability for data-driven QA
Apply agentic AI techniques to accelerate test generation, triage, and root cause analysis
integrate intelligent diagnostics into pipelines
Develop rigorous test cases for low-level features (PCIe, DMA, interrupts, memory management), error handling, recovery, and fault injection

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Lead Automative Use Cases Validation Engineer

Job Description

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