RF Circuit Design Expert

Obsidian; New York (NY); On-site; USD 83,000 - 165,000; Full time

Job summary

Obsidian is seeking an Electrical Engineering & RF/Circuit Design Expert to design graduate-level problems that leverage tools like scikit-rf and ngspice. You will craft tasks that require multi-step scientific workflows, interpret results, and fine-tune difficulty through iterative testing against AI models.

You should have MS or PhD-level training and strong Python skills, with hands-on experience using the specified libraries.

Qualifications

• Graduate-level training in a relevant STEM field (MS, PhD, or equivalent).
• Proven proficiency with at least one of the listed scientific software libraries, demonstrated in publications or work.
• Strong Python skills for writing problem setups, oracle functions, and validators.
• Ability to work independently and refine problem designs based on feedback.
• Comfort working in Linux/terminal environments with remote compute sandboxes.
• Availability for at least 15–20 hours per week.

Responsibilities

• Design original graduate-level problems based on real scientific workflows.
• Use specialized software to construct and validate challenging computational tasks.
• Test problems against state-of-the-art AI models and refine difficulty.
• Plan queries or experiments to uncover non-obvious information from data.
• Iterate problem designs to ensure robust and credible evaluation.

Skills

Python proficiency

RF/Circuit design

problem design

Education

MS or PhD in relevant STEM field

Tools

scikit-rf

ngspice

Job description

Electrical Engineering & RF/Circuit Design Expert

About the Project

We're building a large-scale benchmark to test how well advanced AI systems can solve hard scientific and engineering problems. As a task designer, you'll create challenging computational problems that check whether AI can use real scientific software to do research-level work — running simulations, interpreting results, designing experiments, and uncovering hidden information from data.

This isn't a typical data-labeling job. You'll design original, graduate-level problems based on real scientific workflows, test them against cutting-edge AI models, and fine-tune them until the difficulty is just right.

What You'll Do

You'll create problems that require skilled use of specialized scientific software. Some will ask the AI to compute exact answers from a fully defined setup — testing whether it can correctly carry out complex, multi-step workflows. Others will be harder: the AI must plan a series of queries or experiments to uncover information that isn't directly visible, which means thinking strategically about what to measure, how to read partial results, and how to narrow down the possibilities efficiently.

Each problem goes through a testing loop against state-of-the-art AI models, and you'll refine it until it hits the target difficulty.

Domains & Tools We're Hiring For

We're especially interested in experts with deep, hands-on experience in:

Electrical Engineering & RF/Circuit Design

working with scikit-rf for RF and microwave network analysis, S-parameter characterization, and transmission-line modeling, or ngspice for circuit simulation, operating point analysis, and frequency response characterization. Candidates should be comfortable designing problems that involve recovering circuit parameters from measurement data.

Experience with other specialized software in this domain will also be considered.

What Makes a Strong Candidate

You have graduate-level expertise (MS or PhD preferred) in the domain above, with real hands‑on experience using these tools — not just theoretical knowledge. You've written code using these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard rather than just complicated.

Beyond domain expertise, the best candidates think like puzzle designers: building problems where the challenge comes from smart reasoning rather than raw computation, where several approaches seem plausible but only careful analysis reveals the right one, and where surface‑level pattern matching won't get you to the answer.

Requirements

• Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience)

• Proven proficiency with at least one of the listed scientific software libraries, shown through research publications, open-source contributions, or professional work
• Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators
• Ability to work independently and refine problem designs based on feedback
• Comfortable working in a Linux/terminal environment with remote compute sandboxes
• Available for at least 15–20 hours per week

Nice to Have

• Experience across multiple listed domains or tools
• Familiarity with benchmark or evaluation design
• Background in scientific teaching or exam/problem-set design
• Experience with computational reproducibility and containerized environments