Research Engineer

$89K - $99K Marina del Rey, CA, US Mid Level Research Engineer

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Skills & Technologies

KerasPythonPytorchTensorflowTransformers

About This Role

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The USC Mark and Mary Stevens Neuroimaging and Informatics Institute and Laboratory of Neuro Imaging (INI, www.ini.usc.edu) are world leaders in the development of advanced computational and scientific approaches for the comprehensive mapping of brain structure and function. LONI’s unique multidisciplinary environment and cutting-edge resources allow for integration of clinical, psychological and genotypic information with neuroimaging phenotypes for research questions in neurology, psychiatry and developmental neurobiology.

The Mark and Mary Stevens Neuroimaging and Informatics Institute is recruiting a talented full-time Research Engineer to help with various projects on neurodegenerative disorders. Under the supervision of the PI, the candidate will assist with data processing, analyzing the data, applying machine learning, generative AI and ensemble integration methods to the datasets, data visualization for interpretability of the models, submit abstracts and papers to conferences and assist in preparing manuscripts.

Designs, develops, and tests materials and prototypes for research projects. Investigates the feasibility of applying specific scientific principles and concepts to potential inventions and projects. Analyzes and presents data as appropriate and makes decisions to further the goals of the experiment.

Primary responsibilities will include working with large scale databases to identify and provide trajectories of brain decline. The candidate is expected to provide thorough documentation of methods publicly on GitHub, and be comfortable training coworkers in the methodologies. Tasks also include writing conference papers and assisting in manuscript preparation. The candidate will be responsible for working within the scope of funded projects, including but not limited to brain mapping in aging and Alzheimer’s disease.

Required Qualifications:

  • Master’s Degree in Electrical Engineering/Biomedical Engineering/Computer Science/Data Science and 3+ years of experience in neuroimaging.
  • Strong understanding of machine learning, deep learning for biomedical imaging, computer vision, Generative AI and ensemble integration of artificial intelligence methods, statistics and image processing.
  • Experience working with large-scale neuroimaging and genetics data.
  • Proficiency in oral and written communication as determined by contributions to scientific conferences and related presentations.
  • Supervise assigned student workers for completion of a project.
  • Experience in designing, developing and maintaining pipelines/tools using machine learning and deep learning for neuroimaging applications.
  • Knowledge about data visualization and various data analytics tools and libraries.

Preferred Qualifications:

  • 5+ years of experience in applications of AI in neuroimaging.
  • Experience in working on projects related to aging of the brain to predict the structure of the brain as a function of sociodemographic and genetic factors.
  • Experience building raw or segmented MR image quality assessment tools using machine learning and deep learning.
  • Experience with synthetic data generation using generative models for harmonization of imaging data from multiple sources/sites using deep generative networks.
  • Knowledge about ML models for classification and regression, deep learning networks like CNN’s, RNN’s, autoencoders and generative models like GANs, diffusion models, vision transformers.
  • Experience writing and distributing code in Python, R, matlab, C/C++ or similar languages.
  • Experience with ML frameworks such as PyTorch, Tensorflow, Keras, etc.
  • Contribution to ISBI, ISMRM, OHBM, MICCAI, SIPAIM, EMBC or other AI in medical imaging and related conferences.

The annual base salary range for this position is $89,291.89 - $99,000.00. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate’s work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.

The university is committed to maintaining a safe and secure environment for students, employees, volunteers, and visitors on our campuses and those entrusted to our care, including patients, students, and minors. To that end, the university conducts background screening, including screening for criminal convictions, on all applicants after a conditional offer of employment and as a condition of employment. Please refer to the Background Screening Policy Appendix C for specific employment screen implications for the position you are applying for.

Minimum Education: Master's degree In Engineering Or in related field(s)

Minimum Experience: 3 years

Minimum Skills: Experience in a laboratory setting conducting scientific research. Excellent written and oral communication skills. Ability to communicate technical information to non-technical audiences.

Preferred Education: Doctorate

Preferred Experience: 5 years

Preferred Skills: Proven experience achieving results in a scientific research environment. Deep knowledge base in specific field.

USC is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other characteristic protected by law or USC policy. USC observes affirmative action obligations consistent with state and federal law. USC will consider for employment all qualified applicants with criminal records in a manner consistent with applicable laws and regulations, including the Los Angeles County Fair Chance Ordinance for employers and the Fair Chance Initiative for Hiring Ordinance, and with due consideration for patient and student safety. Please refer to theBackground Screening Policy Appendix Dfor specific employment screen implications for the position for which you are applying.

We provide reasonable accommodations to applicants and employees with disabilities. Applicants with questions about access or requiring a reasonable accommodation for any part of the application or hiring process should contact USC Human Resources by phone at (213) 821-8100, or by email at [email protected]. Inquiries will be treated as confidential to the extent permitted by law.

  • Notice of Non-discrimination
  • Employment Equity
  • Read USC’s Clery Act Annual Security Report
  • USC is a smoke-free environment
  • Digital Accessibility

If you are a current USC employee, please apply to this USC job posting in Workday by copying and pasting this link into your browser:

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Salary Context

This $89K-$99K range is in the lower quartile for Research Engineer roles in our dataset (median: $192K across 50 roles with salary data).

View full Research Engineer salary data →

Role Details

Title Research Engineer
Location Marina del Rey, CA, US
Experience Mid Level
Salary $89K - $99K
Remote No

About This Role

Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.

The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.

Across the 9,653 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Keck Medicine of USC, this role fits into their broader AI and engineering organization.

Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.

What the Work Looks Like

A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.

Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.

Skills Required

Keras Python (17% of roles) Pytorch (5% of roles) Tensorflow (4% of roles) Transformers (1% of roles)

Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.

Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.

Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.

Compensation Benchmarks

Research Engineer roles pay a median of $252,000 based on 419 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($94K) sits 63% below the category median. Disclosed range: $89K to $99K.

Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and AI Engineering Manager ($251,622). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.

Keck Medicine of USC AI Hiring

Keck Medicine of USC has 2 open AI roles right now. They're hiring across Data Scientist, Research Engineer. Positions span Los Angeles, CA, US, Marina del Rey, CA, US. Compensation range: $99K - $148K.

Location Context

Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).

Career Path

Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.

From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.

This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.

What to Expect in Interviews

Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.

When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.

AI Hiring Overview

The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.

The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).

Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.

The AI Job Market Today

The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 419 roles with disclosed compensation, the median salary for Research Engineer positions is $252,000. Actual compensation varies by seniority, location, and company stage.
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
About 6% of the 9,653 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Keck Medicine of USC is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from Research Engineer positions include Senior Research Engineer, Research Scientist, ML Architect. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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