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Ai Research Engineer Jobs (NOW HIRING)

OpenAI

Research Engineer

San Francisco, CA · On-site

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. As a Research Engineer, you will be responsible for ...

Netic

Applied AI Research Engineer

San Francisco, CA · On-site

As an Applied AI Research Engineer, you'll dive deep into cutting-edge research, understand the business functions we put on autopilot inside-out, and execute targeted ML projects that deliver pure ...

Chai Discovery, Inc

Research Engineer

San Francisco, CA · On-site

AI is reinventing life sciences the same way it reinvented software engineering, and Chai is at the ... About the role We are seeking an AI Research Engineer to help design, train, evaluate, and optimize ...

Trunk Tools

AI Research Engineer- Speech 1

Redmond, WA · On-site

$229K/yr

About Job AI Engineer: Speech/Audio Centific AI Research About Centific AI Research Centific AI Research is at the forefront of developing cutting-edge AI solutions that bridge the gap between ...

Hume AI

Senior/Staff AI Research Engineer

San Jose, CA · On-site +1

$180K - $350K/yr

Hume AI is seeking talented researchers and engineers interested in working with our AI research team to build state-of-the-art speech-language models (SLMs). Our new SLM training method ...

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$106K

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How much do ai research engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for ai research engineer in the United States is $106,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $104,000.00 per year, depending on experience, location, and employer.

What does an AI Research Engineer do?

An AI Research Engineer designs, develops, and tests artificial intelligence models and algorithms. They work on advancing the state-of-the-art in machine learning, deep learning, and related fields, often collaborating with data scientists and software engineers. Their responsibilities typically include experimenting with new approaches, implementing prototypes, publishing research findings, and helping to integrate AI solutions into products or services. The role requires strong programming skills, a deep understanding of mathematics and statistics, and the ability to keep up with rapid advancements in AI technology.

What are the key skills and qualifications needed to thrive as an AI Research Engineer?

To thrive as an AI Research Engineer, you need strong expertise in mathematics, machine learning algorithms, programming (especially Python), and typically a graduate degree in computer science or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience using large datasets, and sometimes knowledge of cloud computing platforms are commonly required. Creativity, problem-solving abilities, and effective collaboration are crucial soft skills that distinguish top performers in this role. These skills and qualities are essential for developing innovative AI models, solving complex research problems, and contributing impactful solutions in a rapidly evolving field.

What are some common challenges AI Research Engineers face when transitioning research models into production environments?

AI Research Engineers often encounter challenges when moving models from research to production, such as ensuring scalability, optimizing for real-world data variability, and maintaining model performance under resource constraints. Additionally, integrating research models with existing systems and workflows can require close collaboration with software engineers and data engineers. Addressing issues like reproducibility, monitoring, and model retraining is crucial for long-term success in production settings. Proactive communication and a strong understanding of both research and engineering principles help overcome these hurdles.

What is the difference between Ai Research Engineer vs Data Scientist?

AspectAi Research EngineerData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with machine learning frameworksDegree in Statistics, Computer Science, or related fields; strong analytical skills
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics teams, data-driven companies, consulting firms
Employer & Industry UsageTech companies, research institutions, AI startupsFinance, healthcare, marketing, e-commerce
Common Search & Comparison IntentUnderstanding roles in AI research and developmentAnalyzing data to inform business decisions

While both roles involve working with data and algorithms, Ai Research Engineers focus on developing new AI models and advancing AI technology, often in research settings. Data Scientists analyze and interpret complex data to help organizations make strategic decisions. The roles overlap in skills like programming and machine learning, but their primary goals and work environments differ.

How much do AI research engineers make?

AI research engineers typically earn between $100,000 and $150,000 annually, with salaries increasing based on experience, education, and location. Senior roles or those with specialized skills in deep learning, natural language processing, or machine learning frameworks can earn higher salaries, often exceeding $200,000.
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Ai Research Engineer jobs near you
Infographic showing various Ai Research Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $106,012 per year, or $51 per hour.

AI Research Engineer, Pre-Training

Hudson River Trading

London, CA • On-site

Full-time

Re-posted 7 days ago

Job description

Hudson River Trading (HRT) is seeking an AI Research Engineer (Pre-training) to join the HAIL team. HAIL (HRT AI Labs) is the team at HRT responsible for developing and maintaining our most powerful models, which are used by our trading teams to drive a significant fraction of our trading. We are building and deploying "foundation models for markets", that ingest and train on vast amounts of market and "alternative" data (such as language) to make predictions about future market state.

As a pre-training research engineer on HAIL, you will have a general mandate to improve all aspects of large-scale model training, including but not limited to kernel development, training data loading, parallelism, networking, and fault-tolerance. You will work closely with our researchers to co-design and improve our models, and shape the research agenda.

We have multiple large, modern, and rapidly growing GPU clusters, and we maintain a very high GPU-to-researcher ratio. We are simultaneously pursuing multiple strategies and developing many model types with different purposes, and we are strongly incentivized to squeeze as much as we can out of our systems. Your work will be directly, clearly, and highly impactful on the business, and it will be challenging: this is a field with no easy or obvious solutions.

Qualifications

  • Strong engineering skills, especially any of: CUDA/Triton/Pallas/CuTe DSL kernel development, lower-level PyTorch/JAX/XLA development, CUDA Graphs, FPGA/ASIC experience
  • Must have two or more years work experience building deep learning systems, for any domain: robotics, biology, chemistry, physics, audio, video, recommendations, etc.
  • Experience translating methods between areas of application is highly valued
  • LLM experience is valuable, but not necessary
  • Finance experience is not required

The estimated base salary range for this position is 250,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

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