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If you are looking for a challenging and exciting career in the world of technology, then look no further. Skyworks is an innovator of high performance analog semiconductors whose solutions are powering the wireless networking revolution. At Skyworks, you will find a fast-paced environment with a strong focus on global collaboration, minimal layers of management and the freedom to make meaningful contributions in a setting that encourages creativity and out-of-the-box thinking. We are excited about the opportunity to work with you and glad you want to be part of a team of talented individuals who together can change the way the world communicates. Requisition ID: [[id]] Description We are building an intelligent analog and mixed-signal design automation flow that applies agentic AI and machine learning to modernize design and verification practice. You will join a central engineering team developing a next-generation, AI-enabled design and verification platform for complex analog/mixed-signal and RF products and modules - from die-level blocks to integrated module architectures. This role calls for an engineer who has built UVM verification environments and has an automation mindset to encode that expertise into scalable flows. You will inform how the platform reasons about testbenches, coverage, and regressions, and guides engineers through complex digital and mixed-signal verification workflows. Your job is to bridge proven DV practice and new automation so the platform stays grounded in how high-performance products are verified and signed off. Responsibilities Design and deploy ML inference models for engineering use cases: prediction, classification, anomaly detection, and recommendation over design/simulation data Build data engineering pipelines to ingest, clean, label, and version datasets from design and layout databases, as well as simulation and physical verification results Develop LLM-based applications with chain-of-thought prompting for guided troubleshooting, documentation Q&A, and methodology assistance Implement MLOps practices: model versioning, A/B testing, monitoring for drift, and reproducible training pipelines Create APIs and services that integrate ML capabilities into existing EDA and engineering platforms Collaborate with domain experts to define features, labels, and evaluation metrics grounded in engineering outcomes Stay current with industry-standard techniques in deep learning, transformers, and efficient inference Required Experience and Skills B.S. or higher in Electrical Engineering, Computer Engineering, or Computer Science 3+ years of professional digital design verification experience Strong experience building SystemVerilog/UVM testbenches (architecture, agents, scoreboards, coverage) - not only writing tests in an existing environment Strong experience with scripting languages (Python, Bash) Strong debugging and analytical skills Excellent communications skills with the ability to work and thrive in a team environment Desired Experience and Skills Simulator and regression experience (VCS, Xcelium, Questa, or equivalent) including batch/farm runs Assertions (SVA), formal, or mixed-signal / AMS co-verification Experience creating, verifying, and simulating with behavioral models for analog circuits. Automation for testbench setup, results parsing, coverage reporting, or regression orchestration Proficiency with git version control and CI/CD pipelines Practical ML/AI skills: Python-based development with frameworks such as PyTorch, TensorFlow, or LangChain/LlamaIndex (or equivalent); experience building LLM applications, RAG pipelines, or ML inference services Experience building or integrating agentic workflows that call EDA tools (simulation, formal, job schedulers) as tools in a loop Scripts that integrate with HPC/job farms for batch simulation or regression Interest in applying ML to verification artifacts (coverage, logs, traces, test stimulus) beyond text-only LLM use #LIPR1 Skyworks is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.