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Full Time Machine Learning Researcher Jobs (NOW HIRING)

Inference

Machine Learning Researcher

San Francisco, CA · On-site

$250K - $350K/yr

Perform reinforcement learning research to improve model alignment and capability * Develop and improve our distillation pipeline for training high-quality models from frontier teachers * Train ...

Droyd

Lead Machine Learning Researcher

San Francisco, CA · On-site

$196K/yr

This work runs on real machines, not benchmarks. About the role As an AI Researcher at Droyd, you'll own meaningful parts of the learning and inference stack that power our robotic arms. You'll train ...

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Full Time Machine Learning Researcher information

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$30K

$113.1K

$164.5K

How much do full time machine learning researcher jobs pay per year?

As of Jun 19, 2026, the average yearly pay for full time machine learning 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.

Which 5 jobs will survive AI?

Full Time Machine Learning Researchers are likely to continue to find roles in developing and improving AI systems, as their expertise in designing algorithms and models remains essential. Jobs that require complex problem-solving, creativity, and human judgment, such as healthcare professionals, educators, skilled tradespeople, and certain managerial roles, are also expected to persist despite AI advancements. These roles often involve tasks that are difficult for AI to fully replicate or replace.

What is the difference between Full Time Machine Learning Researcher vs Data Scientist?

AspectFull Time Machine Learning ResearcherData Scientist
CredentialsAdvanced degrees in CS, ML, or related fieldsDegree in CS, statistics, or related fields; often includes certifications
Work EnvironmentResearch labs, academic institutions, R&D departmentsBusiness environments, tech companies, analytics teams
Industry UsagePrimarily in research-focused roles, developing new algorithmsApplying models to solve business problems, data analysis

While both roles require strong technical skills and knowledge of machine learning, Full Time Machine Learning Researchers focus on developing new algorithms and advancing ML theory, often in research settings. Data Scientists apply existing models to analyze data and generate insights for business decisions. The roles overlap in skills but differ in focus and work environment.

Which 3 jobs will survive AI?

Full Time Machine Learning Researchers are likely to continue to find roles in developing and improving AI systems, as their expertise in designing algorithms and models is essential. Other jobs expected to survive AI include healthcare professionals like doctors and nurses, who require human judgment and empathy, and skilled trades such as electricians and plumbers, which involve hands-on work difficult to automate fully.

Is ML research oversaturated?

Full-time machine learning research positions are competitive due to high demand for AI expertise, but opportunities continue to grow as industries adopt AI solutions. Success often depends on strong technical skills, research experience, and staying current with advancements in algorithms and tools like Python and TensorFlow.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning researcher or executive role, often involving advanced skills in deep learning, data analysis, and programming. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or research contributions in cutting-edge AI projects.
More about Full Time Machine Learning Researcher jobs
What are the most commonly searched types of Machine Learning Researcher jobs? The most popular types of Machine Learning Researcher jobs are:
What job categories do people searching Full Time Machine Learning Researcher jobs look for? The top searched job categories for Full Time Machine Learning Researcher jobs are:
Full Time Machine Learning Researcher jobs near you
Infographic showing various Full Time Machine Learning Researcher job openings in the United States as of June 2026, with employment types broken down into 62% Part Time, and 38% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

Machine Learning Researcher - Springtail

Astera

Emeryville, CA • On-site

$150K - $300K/yr

Full-time

Posted 24 days ago

Job description

About Astera
Astera is a private foundation on a mission to steer science and technology toward an abundant future. We believe the coming years will bring an era of unprecedented scientific and technological advancement as exponential progress in AI converges with central advances in other fields to dramatically accelerate innovation. This inflection point provides an unparalleled opportunity to fundamentally rethink the institutions, systems, and tools that drive scientific progress.
Unlike traditional non-profit research organizations, Astera funds and operates projects like high-velocity startups, allowing us to focus on ambitious goals, match structure to problem, and attract strong technical talent and leadership. You can read more about our mission, vision, and programming here.
Position Summary
Datasets in many areas, science in particular, are often small, heterogeneous, and expensive. Human scientists can take these datasets and generate models to describe them, but this process of model induction is labor-intensive and error-prone. Machine learning is a general and scalable solution, but it is not uniformly sample efficient.
The Astera Institute is seeking a Machine Learning Researcher to help surmount this barrier with new architectures for data-efficient and general model induction. This includes bootstrapped program synthesis, along with components for a system that synthesizes its own learning algorithms - a machine learning strange loop. This is a full time position that reports to Timothy Hanson.
Responsibilities
  • Hypothesize, test, and refine means of improving generalization performance of common architectural elements, including different forms of attention. This includes devising controlled datasets to elucidate e.g. learning order & learned representations.
  • Think both mathematically and empirically about problems of runtime inference in gradient-trained networks, with an eye to the extensive literature on statistical learning and an open mind to the many forms of constrained optimization.
  • Contribute to a well-documented and well-instrumented code base that is performant where necessary yet expeditious where experimental throughput demands.

Qualifications and Experience
  • Masters or equivalent in machine learning, mathematics, or equivalent fields (strong candidates from neuroscience are encouraged to apply).
  • Fluency with Pytorch, and familiarity with JAX, CUDA, and/or Triton + their open-source ecosystems.
  • Demonstrated ability do fundamental research.
  • Demonstrated ability to work in teams.

Location
This position is hybrid at our office in Emeryville, CA. Some travel may be required from time-to-time for in-person collaboration and work.
Compensation
The posted salary range is based on location in the Bay Area. The successful candidate will receive a competitive compensation package, commensurate with their experience and location.
  • Benefits summary

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