AI ML Engineer

At Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future. We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster.

We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.

We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace.

Key Responsibilities

- Hands-on experience with hardware verification methodologies and front-end design verification flows.

- Experience with HDL languages (SystemVerilog, Verilog) and verification frameworks (UVM/OVM).

- Experience with AI-powered development tools such as Claude, Claude Code, and MCP (Model Context Protocol) for automating and accelerating verification tasks.

- Proficiency in integrating LLM-based assistants into engineering workflows to improve productivity and code quality.

- Familiarity with machine learning concepts including supervised/unsupervised learning, neural networks, and their application to verification tasks (e.g., coverage closure, bug prediction, test generation).

- Building reusable verification components and libraries for future use.

- Candidate must have good analytical and problem-solving skills.

- Knowledge of simulation, debugging, and waveform analysis tools is good to have

- Knowledge of scripting languages (Python, Tcl, Perl) is good to have.

Additional Skills

 - Strong understanding of C/C++ language is good to have.

- Familiarity with version control systems (Git) and CI/CD workflows.

- Exposure to RAG (Retrieval-Augmented Generation) and AI-driven document/knowledge management tools.