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Gold Diving information

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$11K

$56.8K

$144K

How much do gold diving jobs pay per year?

As of Jun 12, 2026, the average yearly pay for gold diving in the United States is $56,841.00, according to ZipRecruiter salary data. Most workers in this role earn between $25,000.00 and $46,000.00 per year, depending on experience, location, and employer.

What is gold diving?

Gold diving is a method of underwater gold mining where divers use specialized equipment to search for and extract gold from riverbeds, ocean floors, or other bodies of water. Divers typically use suction dredges or hand tools to collect gold-bearing sediments, which are then processed to separate the gold from other materials. This type of mining is physically demanding and can be hazardous due to cold water, strong currents, and the need for scuba gear or surface-supplied air. Gold diving is most commonly practiced in regions known for placer gold deposits, such as Alaska or parts of Africa. It offers the potential for high rewards but also comes with significant risks and environmental considerations.

What are some common challenges faced by gold divers, and how can they be managed safely?

Gold divers often face challenges such as harsh weather conditions, limited underwater visibility, and the risks associated with operating heavy dredging equipment. These challenges require strict adherence to safety protocols, use of reliable diving gear, and ongoing communication with the surface team. Divers also need to stay physically fit and maintain situational awareness to mitigate hazards like strong currents and equipment malfunctions. Teamwork and thorough pre-dive planning are essential for ensuring safe and effective operations.

What is the difference between Gold Diving vs Gold Mining?

AspectGold Diving
Required CertificationsCommercial Diving Certification, CPR, First Aid
Work EnvironmentUnderwater, in water bodies, often offshore or in rivers
Employer & Industry UsageMining companies, underwater construction, salvage operations
Common Search & ComparisonPeople compare Gold Diving with Gold Mining due to related industry and resource extraction

Gold Diving involves underwater work to recover gold deposits directly from water bodies, requiring specialized diving certifications and underwater skills. Gold Mining typically refers to surface or underground extraction of gold from land, involving different equipment and certifications. Both roles are part of the gold resource industry but differ significantly in environment and techniques.

What are the key skills and qualifications needed to thrive as a Gold Diver, and why are they important?

To thrive as a Gold Diver, you need strong swimming ability, knowledge of underwater mining techniques, and relevant diving certifications such as PADI or commercial diving credentials. Familiarity with underwater metal detectors, dredging equipment, and diving safety systems is typically required. Attention to detail, resilience, and effective teamwork are crucial soft skills in this demanding environment. These skills ensure safe operations, efficient extraction, and successful collaboration in often challenging underwater conditions.
More about Gold Diving jobs
What job categories do people searching Gold Diving jobs look for? The top searched job categories for Gold Diving jobs are:
Gold Diving jobs near you
Infographic showing various Gold Diving job openings in the United States as of June 2026, with employment types broken down into 4% As Needed, 61% Full Time, 18% Part Time, and 17% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $56,841 per year, or $27.3 per hour.

AI QA Engineer (Multilingual)

Scaled Cognition

Mountain View, CA • Remote

Full-time

Posted yesterday

Job description

AI QA Engineer (Multilingual)

As an AI QA Engineer (Multilingual) at Scaled Cognition, you will be the final line of defense for our model's quality. You'll sit at the critical intersection of data engineering, quality assurance, and linguistics, ensuring our LLM training data and evaluation sets are flawless. You'll be getting your hands dirty, meticulously inspecting data, and making direct code contributions to fix issues. If you love the idea of turning messy, imperfect data into gold and have the technical chops to automate parts of that cleanup, you will thrive here.

What you'll do:

  • Meticulously inspect, review, and grade LLM training data, evaluation test cases, and model outputs to ensure maximum quality and accuracy.

  • Maintain local development environments to run test pipelines, investigate edge cases, and submit PRs via Git/GitHub to update our training repositories.

  • Act as a technical data detective, diving deep into training data to spot error cases.

  • Leverage LLMs as internal tools to translate, verify, and maintain our cross-lingual datasets.

  • Collaborate closely with the engineering team to refine our evaluation criteria and improve our data pipelines.

You might be the right person for the job if you:

  • Have an obsessive attention to detail and get a dopamine hit from finding the one edge case or bad translation that broke a prompt.

  • Are a builder who doesn't mind the weeds. You understand that high-quality AI is built on rigorous, sometimes repetitive data inspection, and you embrace that reality.

  • Are technically self-sufficient. You’re comfortable navigating a terminal, running Python scripts locally, and managing your own version control.

  • Love languages and understand the linguistic nuances required for high-quality translation and cross-lingual model evaluation.

  • Thrive in a fast-paced environment where you can take ownership of the data quality that directly drives model performance.

Key Qualifications:

  • Strong technical background with hands-on coding experience (Python preferred) and proficiency with Git/GitHub.

  • Fluency in English and native or near-native proficiency in at least one other language.

  • Deep understanding of Large Language Models, their failure modes (hallucinations, formatting errors), and effective prompting techniques.

  • Proven experience in Quality Assurance, Data Quality, or Data Engineering, with a track record of auditing and maintaining large datasets.

  • Exceptional written communication skills across multiple languages.