Dirt Operator Journey (Grader) Bechtel CorpDirt Operator Journey (Grader)CA941101No5507212310.00.018-Aug-2026Dirt Operator Journey (Grader)Operates dirt moving equipment including but limited to dozers, track hoes, backhoes, and front end loaders. Typically requires a minimum of 48 months of industrial construction experience.30685BRKilby Pecos, Texas Day Shift.
NewDirt Operator Journey (Motor Grader/Bulldozer) Bechtel CorpDirt Operator Journey (Motor Grader/Bulldozer)CA941935No5507212310.00.009-Sep-2026Dirt Operator Journey (Motor Grader/Bulldozer)Operates dirt moving equipment including but limited to dozers, track hoes, backhoes, and front-end loaders, Motor Grader, Bulldozer. Typically requires a minimum of 48 months of industrial construction experience.31469BRRio Grande LNG Brownsville, Texas Day Shift.
Senior / Staff SWE - Backend (Grader) Recruiting From ScratchSenior / Staff SWE - Backend (Grader)San Francisco, CaliforniaRemoteThe engineering team includes talent from Shopify, HubSpot, DoorDash, Stripe, and high-growth startups , and is focused on building high-scale, reliable, AI-enhanced backend systems. Backed by top-tier investors and generating tens of millions in revenue, the company is building an AI-powered “software factory” for local businesses — starting with restaurants and expanding into broader vertical SaaS.
EECS Grader - Student Hourly University of KansasEECS Grader - Student HourlyBerkeley, CAA completed application consists of the on-line application and a clear indication of which courses you qualify for and would like to grade for. PLEASE INCLUDE THE COURSE NUMBER AND NAME (e.g., EECS 388 EMBEDDED SYSTEMS).
Staff Software Engineer, RL Environments Scale AIStaff Software Engineer, RL EnvironmentsSan Francisco, CA; New YorkThe range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time.
Staff Software Engineer, RL Environments Scale AI, Inc.Staff Software Engineer, RL EnvironmentsSan Francisco, CA$252,000–$315,000 / yearThe range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time.
Staff Software Engineer, RL Environments Scale AI IncStaff Software Engineer, RL EnvironmentsSan Francisco, CA$252,000–$315,000 / yearThe range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. You''ll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time.
Senior Machine Learning Engineer Ambience Healthcare IncSenior Machine Learning EngineerSan Francisco, CA$225,000–$300,000 / yearAmbience was ranked #1 for Improving the Clinician Experience in the KLAS Research Emerging Solutions Top 20 Report, recognized by Fast Company as one of the Next Big Things in Tech, named one of the best AI companies in healthcare by Inc., and selected as a LinkedIn Top Startup in 2024 and 2025. What You'll Do: Build Trustworthy AI Evaluation Systems: Design and own evaluation pipelines for LLM and agentic systems, combining automated graders, regression testing, production feedback, and human evaluation to measure real product quality.
Research, Post-Training Evals Thinking Machines Lab IncResearch, Post-Training EvalsSan Francisco, CADevelop usability evaluations that measure whether models are genuinely useful in real research and product workflows, and partner with the data flywheel to turn evaluation insights into better data and training signals. Improve evaluation correctness, including grader reliability, ambiguous ground truth, evaluator disagreement, false positives and negatives, and gaps between measured and intended behavior.
Senior Software Engineer, RL Environments ParetoSenior Software Engineer, RL EnvironmentsSan Francisco, CaliforniaPartner closely with research labs, turn a rough training goal into a spec you can build against, and push back early when the ask won't produce usable signal. You sit between Pareto's engineering team and the researchers at the labs we work with, close enough to both that you can tell when a training goal and a buildable spec have drifted apart.
NewMember of Technical Staff, Head of Quality PlatoMember of Technical Staff, Head of QualitySan Francisco, CaliforniaHarden Verifiers & Tasks: Build automated red-teaming suites to stress-test task feasibility and verifier integrity, aggressively eliminating reward hacking, grader tampering, and impossible task traps. Gate Final Delivery: Own the final sign-off before environments and datasets ship to frontier labs, auditing trajectories, tasks, and reward dynamics for correctness, feasibility, and signal density.