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Financial planning and analysis to ensure accurate recording and enable decision-making, measurements, budget control and ongoing monitoring. With advanced data analysis capabilities

What will your job look like?
Collecting data from all relevant partners and reflecting financial data in the system and analyzing financial data, perform multiple scenarios, build models and identify trends
Extract major insights and conclusions from the analysis
Provide relevant key partners with main takeaways and recommendations
Supporting the business in decision making
Drive automation of day-to-day work processes and apply AI-oriented thinking to improve efficiency, scalability, and decision-making across existing workflows.

Perform intercompany billing calculations and support the quarterly close process across multiple legal entities within the Amdocs group.
Prepare quarterly analyses, reconciliations, and supporting schedules to ensure accurate reporting of intercompany billing and tax-related balances.
Act as a professional focal point for intercompany billing and corporate accounting tax matters, supporting internal stakeholders and helping drive consistent processes across the group.
Work closely with finance teams across Amdocs group legal entities to collect, review, and analyze tax data and ensure timely quarterly reporting.
Provide ongoing support to maintain strong financial processes and controls, and serve as a reliable accounting partner for corporate tax and intercompany billing topics.

Role Purpose Responsible for managing the Marketing Communications function, including content development, project execution, and cross-functional coordination. The role connects marketing strategy with execution, ensuring consistent messaging, high-quality outputs, and delivery of business objectives. Key Responsibilities MarCom Operations Manage day-to-day MarCom activities, prioritize tasks, and ensure timely execution of plans and deliverables. Content & Marketing Assets Develop, produce, and maintain marketing materials while ensuring brand consistency and quality. Product Launches & Projects Lead Go-To-Market activities and manage cross-functional marketing projects end-to-end. Cross-Functional Collaboration Work with internal teams, subsidiaries, and external partners to support marketing initiatives. Customer Experience Support Create marketing materials supporting customer retention, experience, and growth. Events & Exhibitions Support planning and execution of events, exhibitions, and conferences globally and locally.

The MLIL DataPlane team is looking for a Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration.
Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed models.
This is a ground-up effort with rapidly evolving hardware and software. We are looking for an IC who can write and optimize low-level code for custom hardware, validate model architectures end-to-end, build test and profiling infrastructure, and drive performance across the stack.

Key job responsibilities
- Develop and optimize compute kernels for a custom ML accelerator architecture, targeting production-level performance for large language model inference.
- Implement and validate LLM architectures (decoder-only, mixture-of-experts) end-to-end - from PyTorch model definition through distributed execution on custom hardware.
- Integrate custom accelerator backends into open-source ML serving frameworks (vLLM, PyTorch), including scheduler extensions, memory management, and model parallelism.
- Build and maintain test infrastructure for model correctness validation across CPU, GPU, simulator, and hardware targets.
- Profile and optimize inference workloads - identify bottlenecks, instrument critical paths, and drive latency and throughput improvements from simulation through hardware bringup.
- Own features end-to-end: from design through implementation, testing, and integration into the broader software stack.
- Contribute to CI/CD pipelines that gate model and kernel changes on correctness and performance regressions.