Interested in this Research Engineer role at Gladstone Institutes?
Apply Now →Skills & Technologies
About This Role
Category:
-------------
Science
Lab/Area:
-------------
Theodoris Lab
Description:
----------------
The laboratory of Christina Theodoris, MD, PhD, is seeking a highly motivated AI research engineer with a strong background in computer science and machine learning to join her research program in the Gladstone Institute of Cardiovascular Disease and Gladstone Institute of Data Science and Biotechnology. Our lab is focused on developing novel foundational AI models leveraging large\-scale biological data to understand gene network dynamics and accelerate the discovery of network\-correcting therapeutics.
The applicant must have a B.S. in Computer Science, and/or an M.S. in Computer Science or Machine Learning. The applicant must also have hands\-on experience developing AI models with relevant publications or code repositories to demonstrate their prior work.
The successful applicant will have the opportunity to develop novel AI models for network biology, working closely within our collaborative team of computational and experimental biologists and accessing state\-of\-the\-art GPU computing infrastructure. The research engineer will also have opportunities for career development including publishing their work and presenting their work at conferences.
Overall, the fellow will join a highly collaborative team united in the common goal of developing AI models to advance our understanding of biological systems and improve human health.
Required Qualifications:
- B.S. in Computer Science
- M.S. in Computer Science or Machine Learning would be beneficial
- Advanced competency in Python and Bash
- Experience with PyTorch, GPU computing, HPC computing, Slurm, GitHub
- Prior experience with AI model development
Required Application Materials:
- Curriculum vitae
- Cover letter with a brief statement of research background and future goals / interest in the lab
- Contact information for three references
- GitHub repository or other sample code demonstrating background in AI model development
Salary Range:
Research Technologist I \- $61,326\-$71,185
Research Technologist II\- $75,504 \- $88,634
Gladstone Perks \& Benefits
- *People* –work with talented, committed, and supportive teammates within an organization that values each member of its community.
- *A meaningful place to grow and learn* –whether it’s your professional skills or scientific knowledge, we have the resources and environment to advance either so you can better support Gladstone’s mission to drive a new era of discovery in disease\-oriented science and to mentor tomorrow’s leaders in an inspiring and excellent environment.
- *Healthy work/life balance* –you are highly engaged and productive at work because you can have time to recharge and enjoy a vibrant life outside of work.
- *Compensation* –competitive salary. Title and salary will be commensurate with education and experience.
- *Excellent benefits* –generous medical, dental, vision, retirement plan, paid vacation, commuter benefits, access to free shuttle transportation.
Gladstone is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, sex, religion, national origin, ancestry, age, marital status, medical condition, physical or mental disability, veteran status, sexual orientation, or any other non\-job related characteristic. We make all employment decisions so as to further this principle of equal employment.
Salary Context
This $61K-$88K range is in the lower quartile for Research Engineer roles in our dataset (median: $188K across 44 roles with salary data).
View full Research Engineer salary data →Role Details
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 3,708 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Gladstone Institutes, 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
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 $280,000 based on 147 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($74K) sits 73% below the category median. Disclosed range: $61K to $88K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and AI Architect ($254,798). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Gladstone Institutes AI Hiring
Gladstone Institutes has 1 open AI role right now. They're hiring across Research Engineer. Based in San Francisco, CA, US. Compensation range: $88K - $88K.
Location Context
AI roles in San Francisco pay a median of $277,088 across 810 tracked positions. That's 27% above the national 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.