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Jr Software Test Engineer Jobs in Meridian, MS (NOW HIRING)

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Jr Software Test Engineer information

See Meridian, MS salary details

$45.6K

$92.7K

$139.3K

How much do jr software test engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for jr software test engineer in Meridian, MS is $92,737.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,600.00 and $93,700.00 per year, depending on experience, location, and employer.

What is the difference between Jr Software Test Engineer vs Software Test Engineer?

AspectJr Software Test EngineerSoftware Test Engineer
Required CredentialsAssociate degree or relevant certification, basic testing knowledgeBachelor's degree in CS or related field, more experience
Work EnvironmentEntry-level testing teams, supervised tasksMore autonomous testing roles, complex projects
Employer & Industry UsageStartups, IT companies, software firmsEstablished companies, larger software development teams
Search & Comparison IntentEntry-level testing roles, career progressionMid-level testing positions, skill enhancement

The main difference between a Jr Software Test Engineer and a Software Test Engineer lies in experience, responsibilities, and independence. Jr Software Test Engineers are typically entry-level, focusing on basic testing tasks under supervision, while Software Test Engineers handle more complex testing activities with greater autonomy. Both roles are essential in software development, with the Jr role serving as a stepping stone to more advanced testing positions.

What cities near Meridian, MS are hiring for Jr Software Test Engineer jobs?

Cities near Meridian, MS with the most Jr Software Test Engineer job openings:

Jr Software Test Engineer jobs near you
Infographic showing various Jr Software Test Engineer job openings in Meridian, MS as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, 2% Contract, and 1% Nights. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $92,737 per year, or $44.6 per hour.

AI Agent Trajectory Annotator and Reviewer

Bespoke Labs

Meridian, MS • On-site

$20 - $30/hr

Full-time

Posted 6 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