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Ai Phd Jobs (NOW HIRING)

Weekday AI

Electrical Engineering Expert (PhD)

$100 - $120/hr

We are currently helping hire for one of the leading AI labs (via one of our partners); supporting ... PhD in Electrical Engineering from a top US, UK, Canadian, or European university Work experience ...

Mercor

ML Research Scientist - PhD

New York, NY · Remote

$110 - $145/hr

About the job Mercor connects elite creative and technical talent with leading AI research labs ... ML Research PhD Experts (ICML / NeurIPS / ICLR Publications) Type: Contract Compensation: $110-$145 ...

micro1 AI

Research Consultant - Physics AI

Lubbock, TX · Remote

$80 - $140/hr

Role Title: Physics Expert (PhD / Postdoc) Role Type: Contractor. Location: Remote micro1 is ... No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work

micro1 AI

Research Consultant - Physics AI

Mesquite, TX · Remote

$80 - $140/hr

Role Title: Physics Expert (PhD / Postdoc) Role Type: Contractor. Location: Remote micro1 is ... No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work

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How much do ai phd jobs pay per year?

As of Aug 18, 2026, the average yearly pay for ai phd in the United States is $126,499.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,500.00 per year, depending on experience, location, and employer.

What is the difference between Ai Phd vs Machine Learning Engineer?

AspectAi PhdMachine Learning Engineer
Required CredentialsPhD in AI, Computer Science, or related fieldBachelor's or Master's in CS, Data Science, or related field; some roles prefer PhD
Work EnvironmentResearch labs, academia, R&D departmentsIndustry companies, tech firms, startups
Employer & Industry UsageUniversities, research institutions, R&D divisionsTech companies, finance, healthcare, e-commerce
Common Search & ComparisonYesYes

While both Ai Phd and Machine Learning Engineer roles involve working with AI and machine learning technologies, Ai Phd positions are typically research-focused, often in academia or R&D labs, requiring advanced degrees. Machine Learning Engineers usually work in industry, applying algorithms to real-world problems, often with a bachelor's or master's degree. The choice depends on whether you prefer research or practical application in your career.

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Ai Phd jobs near you
Infographic showing various Ai Phd job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $126,499 per year, or $60.8 per hour.

Research Scientist, AI Networking (PhD)

Meta

Menlo Park, CA

$121K/yr

Full-time

Posted 27 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

137th of 245 rated software companies

Job description

In this role, you will be a member of the AI Networking Software team and part of the bigger DC networking organization. The team develops and owns the software stack around NCCL (NVIDIA Collective Communications Library), which enables multi-GPU and multi-node data communication through HPC-style collectives. NCCL has been integrated into PyTorch and is on the critical path of multi-GPU distributed training. In other words, nearly every distributed GPU-based ML workload in Meta Production goes through the SW stack the team owns.At the high level, the team aims to enable Meta-wide ML products and innovations to leverage our large-scale GPU training and inference fleet through an observable, reliable and high-performance distributed AI/GPU communication stack. Currently, one of the team’s focus is on building customized features, SW benchmarks, performance tuners and SW stacks around NCCL and PyTorch to improve the full-stack distributed ML reliability and performance (e.g. Large-Scale GenAI/LLM training) from the trainer down to the inter-GPU and network communication layer. We are seeking engineers to work on the space of GenAI/LLM scaling reliability and performance.
Research Scientist, AI Networking (PhD) Responsibilities:
  • Enabling reliable and highly scalable distributed ML training on Meta's large-scale GPU training infra with a focus on GenAI/LLM scaling

Minimum Qualifications:
  • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
  • Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
  • Specialized experience in one or more of the following machine learning/deep learning domains: High speed networking (RDMA), Distributed ML Training, GPU architecture, ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine Learning frameworks (e.g. PyTorch)
  • Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment

Preferred Qualifications:
  • Knowledge of ML, deep learning and LLM
  • Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences
  • Experience in HPC and parallel computing
  • Knowledge of GPU architectures and CUDA programming
  • Experience with NCCL/RCCL/OneCCL and distributed GPU reliability/performance improvement on RoCE/Infiniband
  • Experience with both data parallel and model parallel training, such as Distributed Data Parallel, Fully Sharded Data Parallel (FSDP), Tensor Parallel, and Pipeline Parallel
  • Experience working and communicating cross-functionally in a team environment
  • Experience in AI framework and trainer development on accelerating large-scale distributed deep learning models
  • Experience working with DL frameworks like PyTorch, Caffe2 or TensorFlow

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$121,992/year to $181,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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