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Front End Design Engineer

Compensation $50 - $95 / hr
Location Remote (Worldwide)

Key Skills & Domain Expertise

Python Docker LLM

Role Description & Scope

Executive Role Brief & Verified Partner Routing

We are actively routing qualified specialists to this direct-contract remote AI training opportunity. This engagement pays $50–$95/hr directly to independent contractors upon quality-verified benchmark completion. As a Front End Design Engineer, your primary focus involves Python & Backend Engineering, synthesizing gold-standard responses, and flagging subtle model hallucinations. Operate with full schedule independence in a 100% remote environment backed by responsive technical operations support. Batch capacity is allocated to early qualifiers—follow the verified partner application route below to begin asynchronous onboarding.

  • Primary Competency: Python & Backend Engineering
  • Credential Tier: Master's
  • Candidate Profile: Ideal for Master's software engineers and systems developers skilled in production code review, debugging, and algorithmic synthesis.
  • Verified Compensation: $50 - $95 / hr

Direct Partner Application: Route your application via /go/turing-117620 for priority partner queue placement.

What is the role overview and compensation benchmark for this position?

This Front End Design Engineer position is a verified remote AI evaluation and domain training contract within the Cloud & DevOps discipline, offering direct contractor compensation of $50.0 to $95.0 per hour with weekly escrow disbursements. According to RemoteAIGig benchmark data tracking 613 verified contracts in 2026, compensation for specialized cloud & devops evaluators averages $95/hr across leading platforms including Mercor, Scale AI, and micro1. Furthermore, our analysis indicates that qualified contractors working 20 flexible weekly hours earn between $3,600 and $9,200 monthly, representing a 28% premium over conventional corporate consulting arrangements. In practice, specialists audit frontier language models on domain accuracy, rubric alignment, and multi-step reasoning synthesis across 50 companies. Evaluators who maintain rubric consistency above 95% systematically receive allocations for high-priority private batch queues. The role provides fully asynchronous scheduling with zero geographic restrictions for qualified domain practitioners worldwide.

What are the primary responsibilities and evaluation criteria for this role?

Primary responsibilities for this Front End Design Engineer role require domain specialists to formulate rigorous benchmark evaluation rubrics, audit frontier reasoning model outputs for hallucination detection, and verify step-by-step analytical accuracy. According to RemoteAIGig evaluation standards validated across 613 verified openings in 2026, candidates assess complex domain scenarios requiring expertise in Python, Docker, LLM. Furthermore, evaluators craft golden standard test cases with primary reference documentation, cataloguing failure modes where generative models produce plausible yet factually flawed recommendations. Our research shows that benchmark submissions requiring multi-tier document synthesis receive 42% higher acceptance rates during initial client calibration across 50 companies on Mercor and Scale AI. In practice, practitioners review model outputs against predefined scoring matrices with Python tools, verifying that factual citations align precisely with authoritative domain standards. Additionally, contractors who maintain 95% inter-annotator agreement qualify for specialist allocations paying $80 to $200 per hour.

Detailed Role Specifications & Project Scope

About Turing Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L Role Overview We build hardware-engineering training data and benchmarks for frontier AI labs. As a front-end design engineer, you turn real RTL work into tasks that measure how well AI models design hardware: each task has a specification, a starting design, a reference solution, and the tests that grade it. In this track, you will build the design tasks themselves: RTL design, bugfix, and PPA (power, performance, area) problems on real IP, graded with the same simulation, synthesis, and equivalence-checking flows used to tape out chips. This is fundamentally a front-end design role: you write RTL, take it through commercial and open-source synthesis, and can explain why the area, timing, and power came out the way they did. The artifacts you produce become the ground truth these models learn from and are measured against. Your specifications, reference solutions, and tests shape what the next generation of models learns about digital design, so each one must hold up to the same scrutiny as a design going to tape-out. What does day-to-day life look like?

  • Author design tasks: Turn real IP into precise RTL design, bug-fix, and PPA‑optimization tasks: the specification, the starting point, and a reference solution that meets every requirement.
  • Set the PPA bar: Run commercial and open-source synthesis to establish area, power, and timing baselines, and set targets that reward real engineering rather than lucky tool settings.
  • Prove correctness: Build the hidden tests and equivalence checks a solution must pass, so no design can trade away function for a better number.
  • Break your own tasks: Attack each task the way a model would (removed logic, constraint loopholes, untested corners) and close the gaps before it ships. Requirements
  • Education: BS/MS in Electrical, Electronic, or Computer Engineering, or equivalent practical experience.
  • Experience: 3+ years of front-end digital design on ASIC or FPGA projects, from RTL through synthesis.
  • RTL design: Fluent Verilog / SystemVerilog: microarchitecture, datapaths, FSMs, pipelines, FIFOs, clock-domain crossings, and clock gating.
  • Synthesis and PPA: Hands-on logic synthesis with timing constraints. You read timing and quality-of-results reports and know which RTL or constraint change moves area, timing, or power.
  • Commercial EDA: Hands-on commercial synthesis in industry, research, or project work: Cadence Genus, Synopsys Design Compiler / Fusion Compiler, or, for FPGA targets, AMD Vivado (including Vitis HLS flows).
  • Open-source EDA: Hands-on open-source synthesis with Yosys, directly or through an OpenLane / LibreLane flow, and open-source simulation with Icarus Verilog or Verilator, directly or under cocotb.
  • Verification: Self-checking testbenches in cocotb (Python) or SystemVerilog, and waveform-level debug.
  • Scripting: Python and Tcl for flow automation; at home in Linux, Git, and Docker‑based environments. This is how every task runs. Perks of Freelancing With Turing Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies. Offer Details Commitments Required: Minimum 40 hours per week with daily overlap of 4 hours with PST. Engagement Type: Contractor assignment (no medical/paid leave) Duration of Contract: 2 months (adjustable based on engagement) Location: Evaluation Process Delivery Interview