2 Xla Jobs

Oracle EBS Financials Functional Analyst to be the focal point for support and enhancement of Oracle EBS Financials business processes. Key activities for this role will include business process refinement, solution design, configuring EBS modules, testing, and end user support for key Finance modules in Trimbles global Oracle environment. The candidate will be a part of the Finance Solutions Delivery organization, and will have technical ownership of all aspects from project implementation to process enhancements to sustaining support. Responsibilities: Work closely with business stakeholders and users to gather the end-user requirements and communicate IT priorities and delivery status to the business units Development of test scenarios and test cases, orchestrate the execution, test run validation of functional user testing Design and development of third party integrations, operational workflows, the development and execution of the roll-out strategies, cut-over plans, end-user training and support and end-user documentation Understand, communicate, and educate on the complexities, interdependencies and data flow of business processes across Oracle EBS finance modules, including GL, AP, AR, CM, FA and ebtax Development of clear functional business requirements/specifications Troubleshooting production issues through discussion with end users and technical resources, including problem recognition, research isolation and resolution steps. Maintain the health and effectiveness of the Oracle platform over time Take ownership of issues and work with business users and the development team to find resolutions Provide day-to-day functional support and troubleshooting including table level SQL research queries Drive open and comprehensive communications with key stakeholders, managing their expectations through clear and frequent communications Maintain and modify configuration, security, and access of Oracle modules Create and maintain application and process documentation, as well as training materials Guide and lead testing activities from unit testing to Production validation Qualifications: Minimum of 8 years of experience with Oracle R12.2 Financials modules, including GL, AP, AR, XLA, CM, FA, EBTax, iExpense, AGIS, Advance Collections Experience working on Oracle Enterprise Command Centers, Lockbox Payments, Customer epayments such as Credit Card or ACH Good understanding of financial tables and SQL technology Strong Subledger accounting knowledge is a must. Should be able to analyze and identify any root causes in case of accounting and during period close issues. Experience with the below modules will be considered a plus, Inventory, Purchasing, OM, Service Contracts, Installed Base Experience with the below tools is a plus, DOMO, Vertex, OneSource, Pagero, Revpro, Getpaid, Cybersource, Runpayments Experience with Salesforce is a plus Must be an effective communicator (written and oral) across all levels of organization, including users, developers and management Must have experience documenting requirements and developing system / user test plans "

General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Systems Engineer, you will research, design, develop, simulate, and/or validate systems-level software, hardware, architecture, algorithms, and solutions that enables the development of cutting-edge technology. Qualcomm Systems Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience. Principal Engineer Machine Learning We are looking for a Principal AI/ML Engineer with expertise in model inference , optimization , debugging , and hardware acceleration . This role will focus on building efficient AI inference systems, debugging deep learning models, optimizing AI workloads for low latency, and accelerating deployment across diverse hardware platforms. In addition to hands-on engineering, this role involves cutting-edge research in efficient deep learning, model compression, quantization, and AI hardware-aware optimization techniques . You will explore and implement state-of-the-art AI acceleration methods while collaborating with researchers, industry experts, and open-source communities to push the boundaries of AI performance. This is an exciting opportunity for someone passionate about both applied AI development and AI research , with a strong focus on real-world deployment, model interpretability, and high-performance inference . Education & Experience: 20+ years of experience in AI/ML development, with at least 5 years in model inference, optimization, debugging, and Python-based AI deployment. Masters or Ph.D. in Computer Science, Machine Learning, AI Leadership & Collaboration Lead a team of AI engineers in Python-based AI inference development . Collaborate with ML researchers, software engineers, and DevOps teams to deploy optimized AI solutions. Define and enforce best practices for debugging and optimizing AI models Key Responsibilities Model Optimization & Quantization Optimize deep learning models using quantization (INT8, INT4, mixed precision etc), pruning, and knowledge distillation . Implement Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) for deployment. Familiarity with TensorRT, ONNX Runtime, OpenVINO, TVM AI Hardware Acceleration & Deployment Optimize AI workloads for Qualcomm Hexagon DSP, GPUs (CUDA, Tensor Cores), TPUs, NPUs, FPGAs, Habana Gaudi, Apple Neural Engine . Leverage Python APIs for hardware-specific acceleration , including cuDNN, XLA, MLIR . Benchmark models on AI hardware architectures and debug performance issues AI Research & Innovation Conduct state-of-the-art research on AI inference efficiency, model compression, low-bit precision, sparse computing, and algorithmic acceleration . Explore new deep learning architectures (Sparse Transformers, Mixture of Experts, Flash Attention) for better inference performance . Contribute to open-source AI projects and publish findings in top-tier ML conferences (NeurIPS, ICML, CVPR). Collaborate with hardware vendors and AI research teams to optimize deep learning models for next-gen AI accelerators. Details of Expertise: Experience optimizing LLMs, LVMs, LMMs for inference Experience with deep learning frameworks : TensorFlow, PyTorch, JAX, ONNX. Advanced skills in model quantization, pruning, and compression . Proficiency in CUDA programming and Python GPU acceleration using cuPy, Numba, and TensorRT . Hands-on experience with ML inference runtimes (TensorRT, TVM, ONNX Runtime, OpenVINO) Experience working with RunTimes Delegates (TFLite, ONNX, Qualcomm) Strong expertise in Python programming , writing optimized and scalable AI code. Experience with debugging AI models , including examining computation graphs using Netron Viewer, TensorBoard, and ONNX Runtime Debugger . Strong debugging skills using profiling tools (PyTorch Profiler, TensorFlow Profiler, cProfile, Nsight Systems, perf, Py-Spy) . Expertise in cloud-based AI inference (AWS Inferentia, Azure ML, GCP AI Platform, Habana Gaudi). Knowledge of hardware-aware optimizations (oneDNN, XLA, cuDNN, ROCm, MLIR, SparseML). Contributions to open-source community Publications in International forums conferences journals