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Ai Researcher In Ethics Jobs (NOW HIRING)

AGI Inc

AI Researcher

San Francisco, CA · On-site

Grounded in years of agent research, our AI is designed with trustworthiness and reliability as core pillars, not afterthoughts. We are supported by tier-1 investors who funded the first generation ...

1X Technologies AS

AI Researcher

San Carlos, CA · On-site

$250K - $350K/yr

About the Lab The 1X World Model Lab is an embodied AI research organization focused on pretraining ... Simply: good tokens in = good tokens out! Data Infrastructure and Tooling Design and operate the ...

Booz Allen Hamilton, Inc.

AI Researcher

Chantilly, VA · On-site

$99K - $225K/yr

AI Researcher The Opportunity: As an analytics professional, you're excited at the prospect of ... You'll grow your skills in AI and ML and shape the future of analytics through a variety of means ...

Booz Allen Hamilton, Inc.

AI Researcher

Chantilly, VA · On-site +1

$99K - $225K/yr

Share AI Researcher The Opportunity: As an analytics professional, you're excited at the prospect ... You'll grow your skills in AI and ML and shape the future of analytics through a variety of means ...

Deeter Analytics Inc

Entrepreneurial AI Researcher

PyTorch/JAX). -Think in systems: data quality, scaling laws, evaluation, and deployment constraints ... What we offer -A well-funded trading firm expanding into AI research - your ideas set direction and ...

Booz Allen Hamilton

AI Researcher

Chantilly, VA

$99K - $225K/yr

AI Researcher The Opportunity: As an analytics professional, you're excited at the prospect of ... You'll grow your skills in AI and ML and shape the future of analytics through a variety of means ...

Booz Allen Hamilton

AI Researcher

Chantilly, VA · On-site

$99K - $225K/yr

R0244539 AI Researcher The Opportunity: As an analytics professional, you're excited at the ... You'll grow your skills in AI and ML and shape the future of analytics through a variety of means ...

Spellbrush

AI Anime Researcher

San Francisco, CA · On-site

The Research Role: We're looking for an experienced AI Researcher to join our team and help us push ... This one of the only labs in the world where you can combine your expertise on anime and deep ...

Spellbrush

AI Anime Researcher

San Francisco, CA · On-site

The Research Role: We're looking for an experienced AI Researcher to join our team and help us push ... This one of the only labs in the world where you can combine your expertise on anime and deep ...

NextDeavor Inc.

Senior AI Researcher

New York, NY · On-site +1

$150K - $220K/yr

Senior AI Researcher Full-time New York, NY, US Exclusive confidential search -- details shared ... Strong Python and PyTorch skills, with experience in distributed multi-GPU training * Clear ...

Distyl AI

Applied AI Researcher, Benchmarking

New York, NY · On-site

$150K - $250K/yr

Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native ...

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How much do ai researcher in ethics jobs pay per year?

As of Aug 17, 2026, the average yearly pay for ai researcher in ethics in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What is an AI researcher in ethics?

AI researchers in ethics are professionals who study and address the ethical implications of artificial intelligence technologies. They analyze how AI impacts society, including issues like bias, privacy, transparency, and accountability. Their work involves developing guidelines, frameworks, and recommendations to ensure responsible AI development and deployment. These researchers often collaborate with technologists, policymakers, and organizations to promote fairness and prevent harm. Their goal is to make sure AI systems benefit society while minimizing potential risks.

What are the key skills and qualifications needed to thrive as an AI researcher in ethics?

To thrive as an AI Researcher in Ethics, you need a strong background in computer science, philosophy, or related fields, often supported by advanced degrees and a solid understanding of both AI technologies and ethical frameworks. Familiarity with programming languages (like Python), machine learning libraries, and ethical AI assessment tools is typically required. Outstanding analytical thinking, communication skills, and interdisciplinary collaboration make someone stand out in this position. These skills and qualities are crucial to ensure the responsible development and deployment of AI systems that align with societal values and mitigate potential harms.

What are some common challenges faced by AI researchers in ethics when collaborating with technical development teams?

AI Researchers in Ethics often encounter challenges when bridging the gap between ethical considerations and technical implementation. One common issue is translating broad ethical principles into specific, actionable guidelines that developers can apply to algorithms and data practices. Additionally, balancing innovation with responsible AI use requires ongoing dialogue, as priorities may differ between ethics and engineering teams. Effective communication and interdisciplinary collaboration are key to ensuring that ethical standards are integrated throughout the AI development lifecycle.

What is the difference between Ai Researcher In Ethics vs Ai Researcher In Fairness?

AspectAi Researcher In EthicsAi Researcher In Fairness
Required CredentialsAdvanced degrees in AI, ethics, philosophy, or related fieldsAdvanced degrees in AI, machine learning, data science, or related fields
Work EnvironmentResearch labs, academia, industry ethics teamsTech companies, research institutions, industry teams
Industry UsageFocus on ethical implications, societal impact, policyFocus on algorithmic bias, equitable outcomes, fairness metrics
Common Search IntentUnderstanding ethical considerations in AI developmentAddressing bias and fairness in AI systems

While both roles involve AI research, Ai Researcher In Ethics emphasizes ethical principles, societal impact, and policy considerations. In contrast, Ai Researcher In Fairness concentrates on reducing bias and ensuring equitable outcomes in AI systems. Both roles often collaborate but focus on different aspects of responsible AI development.

How do I become an AI researcher in ethics?

To become an AI researcher in ethics, you typically need a strong background in computer science, philosophy, or related fields, often holding a master's or doctoral degree. Developing expertise in machine learning, data analysis, and ethical frameworks, along with experience using programming languages like Python, is essential. Engaging in research projects, publishing papers, and staying informed about AI policy and societal impacts are also important steps.

Is AI researcher in ethics a good career?

AI researchers in ethics focus on developing guidelines and frameworks to ensure artificial intelligence is aligned with societal values and safety. The field offers growing opportunities due to increasing AI adoption and the need for ethical oversight, often requiring strong analytical skills and knowledge of AI technologies. It can be a rewarding career for those interested in technology, philosophy, and policy development.
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Ai Researcher In Ethics jobs near you
Infographic showing various Ai Researcher In Ethics job openings in the United States as of August 2026, with employment types broken down into 81% Full Time, 5% Part Time, and 14% Contract. Highlights an 81% In-person, 5% Hybrid, and 14% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

AI Researcher

AGI Inc

San Francisco, CA • On-site

Full-time

Re-posted yesterday

Job description

Think Different. Build the Future.
Our Mission
Build everyday AGI. Trustworthy, consumer-grade agents that redefine human-AI collaboration for millions. Software shouldn't wait for commands; it should partner with you, amplifying what you can do every single day.
Why AGI, Inc.
We're a stealth team of elite founders and AI researchers, with backgrounds spanning Stanford, OpenAI, and DeepMind. We're industry leaders in mobile and computer-use agents, bringing these capabilities to consumer scale.
Grounded in years of agent research, our AI is designed with trustworthiness and reliability as core pillars, not afterthoughts.
We are supported by tier-1 investors who funded the first generation of AI giants; now they're backing us to build the next: everyday AGI. (Watch the demo)
If you see possibility where others see limits, read on.
Make devices think like a frontier model.
Frontier capability inside the compute and memory envelope of a consumer device - phone, laptop, wearable - is not a constraint. It's the most interesting research problem in applied AI today. You'll lead training for one of the model families that powers our on-device agents: pretraining recipe choices, post-training (SFT, RLHF, DPO, GRPO and whatever the next acronym ends up being), distillation, quantization, and the long tail of tricks that make a small model punch above its weight.
This is for the researcher who's tired of training models that go behind an API. You want your model on the device in your pocket, your mom's pocket, and a hundred million pockets you'll never meet.
Tasks you will own
  • One or more model capabilities end-to-end - from data mixture and training objective through eval and shipping into a production on-device runtime
  • The experiment design and writeups that compound across the team - kill what doesn't move the metric, double down on what does
  • A training workstream with a clear success metric and a checkpoint that ships
Areas where you will assist
  • Infra and product engineers, by turning research wins into shipped capabilities
  • Partnerships, by telling them honestly what's possible at the next device refresh and what's not
  • Other researchers, by reading their code and making theirs easier to read
Skills you'll be expected to teach
  • The training techniques that matter most for our regime - distillation from frontier teachers, MoE at small scale, speculative decoding, KV cache compression
  • How to design experiments that move a number you actually care about
Skills you'll be expected to learn
  • What production model deployment looks like under hardware deadlines from OEM partners
  • On-device tool use and agentic post-training at consumer scale
  • The full stack from training run to phone
Timeline of success
After 30 days - You've reproduced one of our recent training runs end-to-end. You've named the three highest-leverage research bets for the next quarter and have a take on which two to run.
After 60 days - You're leading a training workstream with a clear metric. You've shipped a checkpoint that beats the previous best on the eval that matters. People trust your read on what's working.
After 90 days - Your work has shipped into a partner build. You've made one non-obvious bet that paid off and one that didn't, and the team has learned from both. You're shaping the next training cycle.
Compensation
Competitive cash and meaningful equity. Top-tier relocation and immigration support. Permission to publish what's safe to publish. SF, in person.
How to apply
Send a link to your most interesting result - paper, blog, model card, GitHub - with one paragraph on why it matters. Plus your resume, Google Scholar, or LinkedIn. Every exceptional candidate hears back within 48 hours.

Apply