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AI Researcher
San Francisco, CA · On-site
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San Jose, CA · On-site +1
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Ai Researcher information
See salary details
$30K - $42.2K
4% of jobs
$42.2K - $54.5K
3% of jobs
$54.5K - $66.7K
18% of jobs
$67K is the 25th percentile. Wages below this are outliers.
$66.7K - $78.9K
9% of jobs
$78.9K - $91.1K
8% of jobs
$91.1K - $103.4K
3% of jobs
$103.4K - $115.6K
3% of jobs
The median wage is $120.2K / yr.
$115.6K - $127.8K
4% of jobs
$127.8K - $140K
3% of jobs
$140K - $152.3K
3% of jobs
$157.1K is the 75th percentile. Wages above this are outliers.
$152.3K - $164.5K
41% of jobs
$30K
$113.1K
$164.5K
How much do ai researcher jobs pay per year?
As of May 29, 2026, the average yearly pay for ai researcher 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 does an AI Researcher do?
An AI Researcher studies and develops artificial intelligence systems, focusing on advancing machine learning, deep learning, and other AI techniques. They design algorithms, conduct experiments, and analyze data to improve AI models. Their work often involves publishing research papers, collaborating with engineers, and staying updated with the latest advancements in AI.
What are the key skills and qualifications needed to thrive in the Ai Researcher position, and why are they important?
To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually supported by an advanced degree such as a Master's or PhD. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and experience with data analysis tools are commonly required. Critical thinking, effective communication, and a collaborative mindset distinguish top performers in this field. These skills are crucial for understanding complex problems, developing innovative solutions, and sharing findings with multidisciplinary teams.
What does the typical day-to-day work look like for an AI Researcher?
AI Researchers often split their time between developing new algorithms, running experiments, and analyzing results to advance artificial intelligence technologies. They regularly collaborate with data scientists, software engineers, and product teams to ensure their research aligns with practical applications. Literature review and staying current with the latest scientific advancements are also key components of the role. Depending on the organization, AI Researchers may present their findings at conferences or contribute to academic publications, making the position both dynamic and intellectually stimulating.
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Full-time
Posted 16 days ago
Job description
AI Researcher
Location: San Francisco
AboutHum.ai
Hum.ai is building planetary superintelligence. Backed by top funds, we've raised $10M+ and are now heads down building.
Join us at the cutting edge, where we're scaling generative transformer diffusion models, designing next-gen benchmarks, and engineering foundation models that go far beyond LLMs. You'll be at the core of a moonshot journey to define what's next in agentic AI and frontier model capabilities.
We are looking for an experienced AI Researcher who is eager to advance the frontier of AI, help us design, build, and scale end-to-end novel foundation models, and leverage their hands-on experience implementing a wide range of pre-training and post-training models, including large foundation models (beyond just LLM fine-tuning).
Who are we?
Hum is a seed-funded startup on a mission to create positive impact through earth observation and AI. Founded at the University of Waterloo by a team of PhDs and engineers, we're backed by some of the best AI and climate tech investors like HF0, Inovia Capital and Propeller Ventures, angels like James Tamplin (cofounder Firebase) and Sid Gorham (cofounder OpenTable, Granular), and partners like Amazon AWS and the United Nations.
What do we do?
We're building multimodal foundation models for the natural world. We believe there's more to the world than the internet + more to intelligence than memorizing the internet. Our models are trained on satellite remote sensing and real world ground truth data, and are used by our customers in nature conservation, carbon dioxide removal, and government to protect and positively impact our increasingly changing world. Our ultimate goal is to build AGI of the natural world.
The role will involve:
Requirements
Nice to have
Location: San Francisco
AboutHum.ai
Hum.ai is building planetary superintelligence. Backed by top funds, we've raised $10M+ and are now heads down building.
Join us at the cutting edge, where we're scaling generative transformer diffusion models, designing next-gen benchmarks, and engineering foundation models that go far beyond LLMs. You'll be at the core of a moonshot journey to define what's next in agentic AI and frontier model capabilities.
We are looking for an experienced AI Researcher who is eager to advance the frontier of AI, help us design, build, and scale end-to-end novel foundation models, and leverage their hands-on experience implementing a wide range of pre-training and post-training models, including large foundation models (beyond just LLM fine-tuning).
Who are we?
Hum is a seed-funded startup on a mission to create positive impact through earth observation and AI. Founded at the University of Waterloo by a team of PhDs and engineers, we're backed by some of the best AI and climate tech investors like HF0, Inovia Capital and Propeller Ventures, angels like James Tamplin (cofounder Firebase) and Sid Gorham (cofounder OpenTable, Granular), and partners like Amazon AWS and the United Nations.
What do we do?
We're building multimodal foundation models for the natural world. We believe there's more to the world than the internet + more to intelligence than memorizing the internet. Our models are trained on satellite remote sensing and real world ground truth data, and are used by our customers in nature conservation, carbon dioxide removal, and government to protect and positively impact our increasingly changing world. Our ultimate goal is to build AGI of the natural world.
The role will involve:
- Research & Design:
- Deep understanding of current machine learning research.
- Proven track record of generating new ideas or enhancing existing ones in machine learning, evidenced by first-author publications or projects.
- Contribute to research that uncovers the semantics of large datasets, with a focus on earth observation and remote sensing data.
- Ability to independently manage and execute a research agenda, selecting impactful problems and conducting long-term projects autonomously.
- Implementation:
- Developing high-level proof-of-concept (POC) models.
- Experimenting with new state-of-the-art techniques to surpass existing models.
- Plan and execute innovative research and development to push the boundaries of current technology.
- Writing and Publication:
- Assisting in the preparation and writing of technical and scientific papers for publication.
- Demonstrated strong scientific communication/presentation skills.
Requirements
- PhD degree in computer science, engineering, a related field, or equivalent experience.
- Proven track record of successful machine learning research projects
- 5+ years of experience
- Strong scientific understanding of the field of generative AI
- Preference for experience training large diffusion or transformer models, especially on video or time series data.
- Preference for San Francisco or Waterloo, but we're willing to consider remote for great candidates.
Nice to have
- Proficiency in scripting languages such as Python, Bash, or PowerShell.
- Demonstrated experience with deep learning and transformer models.
- Familiarity with designing, pre-training, and fine-tuning large models.
- Proficiency with Python, Ray Trainer, PyTorch, and Anyscale framework.
- Strong technical engineering skills.
- Previous experience in creating high-performance implementations of deep learning algorithms.
- Past training of video or time-series models
- Team player, willing to undertake various tasks to support the team.
- Familiarity with cloud platforms such as AWS, GCP, or Azure.