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Live In Tcu Library Jobs in Portland, ME (NOW HIRING)

Pine Tree Society

Direct Support Professional

Auburn, ME · On-site

$17.50 - $20.50/hr

... to live healthy, socially connected lives. Our program provides a stimulating environment with a ... Some of these activities include picnics in the summer, bowling, and visits to the local libraries ...

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Live In Tcu Library information

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$29.2K

$74.7K

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How much do live in tcu library jobs pay per year?

As of Sep 12, 2026, the average yearly pay for live in tcu library in Portland, ME is $74,671.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,300.00 and $87,500.00 per year, depending on experience, location, and employer.

What does a live in TCU Library staff member do?

A Live In TCU Library staff member typically resides on or near the Texas Christian University campus and is responsible for overseeing library operations during extended hours, assisting students with research, and maintaining a safe and productive environment. Their duties may also include providing customer service, managing library resources, and enforcing library policies. This role is essential for supporting students' academic needs, especially during late nights or special events.

What are the key skills and qualifications needed to thrive as a TCU Library assistant, and why are they important?

To thrive as a TCU Library Assistant, you typically need strong organizational skills, attention to detail, and a background in library science or related experience. Familiarity with library management systems, cataloging software, and digital research tools is commonly required. Excellent customer service, communication, and problem-solving abilities help you support students and faculty effectively. These skills ensure efficient library operations, positive user experiences, and the accurate management of resources.
Live In Tcu Library jobs near you

AI Agent Trajectory Annotator and Reviewer

Biddeford, ME

Bespoke Labs
See more jobs at Bespoke Labsexternal

$20 - $30/hr

Full-time

Posted 12 days ago

Job description

Type: Contract, hourly

Location: Remote

Hours: 20–30 per week

Pay: $20–30/hour, based on experience and language coverage

Start: Immediate

ABOUT THE ROLE

We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision.

You will do two jobs, and you should expect either on any given day.

•Annotate — Read a trajectory nobody has looked at yet and judge it step by step.

• Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it.

TASKS YOU'LL SEE

• Feature build — Add a working feature to a live library without breaking anything that already worked.

• Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects.

• Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them.

Mostly Python and Go, with some Rust, C, and Ct+. A trajectory runs about 100 steps.

WHAT YOU JUDGE IN A TRAJECTORY

• Was the command right for the state the environment was actually in?

• Did the agent read the previous output correctly?

• Was the step wrong, or only inefficient — these are scored differently.

• Where did the run first go off course — usually earlier than where it visibly broke.

• Did the agent notice its own mistake and recover, or keep building on a false assumption?

• Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)?

WHAT WE NEED FROM YOU

• Experience — 2+ years in software engineering, DevOps, or site reliability, with real debugging in real codebases.

• Languages — Strong in Python or Go, and able to read a language you've never used.

• Linux — Comfortable with logs, running processes, build failures, and containers.

• Workflow — Everyday Git, diffs, pull requests, and issue tracking.

• Debugging — Able to work with no test suite and no error message pointing at the cause.

• Focus — Able to hold context across a long run, because step 74 can depend on step 12.

• Writing — Clear English, since every judgement needs an explanation another engineer can check.

Apply