Interested in this Research Engineer role at Chickasaw Nation Industries?
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SUMMARY
The Research Engineer III is a senior professional in the field of research and development. They lead and manage complex research projects, design and execute experiments, analyze data, and contribute to the development of new technologies, products, or processes. They may also provide technical guidance and mentorship to junior research engineers.
Chickasaw Nation Industries, Inc. serves as a holding company with multiple subsidiaries engaged in several lines of business (Business Services, Health, Infrastructure and Engineering, Mission Optimization, Technology and Transportation) for the federal government and commercial enterprises. A portion of our profits is used to support Chickasaw citizens. We are proud to support the economic development and long-term viability of the Chickasaw Nation and its people. CNI offers premium benefits eligible on the first day of hire to full time employees; (Medical - Dental – Vision), Company Life Insurance, Short-Term and Long-Term Disability Insurance, 401(K) Immediate Vesting, Professional Development Assistance, Legal Aid Assistance Program, Family Planning / Fertility Assistance, Personal Time Off, and Observance of Federal Holidays.
As a federal contractor, CNI is a drug-free workplace and adheres to the Federal Controlled Substance Act.
ESSENTIAL REQUIREMENTS
Must possess appropriate level of certifications for this position as required by the contract.
Must be able to obtain and maintain the required customer clearance for access to systems, facilities, equipment and property.
KEY DUTIES AND RESPONSIBILITIES
Essential Duties and responsibilities include the following. Other duties may be assigned.
Leads and manages complex research projects from conception to completion.
Designs and develops innovative research methodologies, experimental protocols, and test plans.
Conducts experiments, collects data, and analyzes results using advanced tools and techniques.
Interprets research findings and draw conclusions to support the development of new technologies, products, or processes.
Collaborates with cross-functional teams to integrate research findings into practical applications.
Contributes to the design and construction of prototypes or experimental setups.
Performs tests and measurements to evaluate the performance of prototypes or experimental systems.
Documents experimental procedures, results, and observations accurately.
Troubleshoots technical issues and propose solutions based on research findings.
Stays updated with the latest advancements in the field through literature reviews, attending conferences or seminars, and networking with experts.
Mentors and provides technical guidance to junior research engineers.
Prepares technical reports, presentations, and publications to communicate research findings.
EDUCATION AND EXPERIENCE
Master's degree and four to seven (4-7) years relevant experience or equivalent combination of education/experience.
PHYSICAL DEMANDS
EOE including Disability/Vet
The estimated pay range for this role is $87K to $95K, with the final offer contingent on location, skillset, and experience.
CNI offers a comprehensive benefits package that includes:
- Medical
- Dental
- Vision
- 401(k)
- Family Planning/Fertility Assistance
- STD/LTD/Basic Life/AD&D
- Legal-Aid Program
- Employee Assistance Program (EAP)
- Paid Time Off (PTO) – (11) Federal Holidays
- Training and Development Opportunities
Your application submission will be considered for all potential employment opportunities with Chickasaw Nation Industries (CNI)
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 9,653 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Chickasaw Nation Industries, 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 in Demand for This Role
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.
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.
Chickasaw Nation Industries AI Hiring
Chickasaw Nation Industries has 1 open AI role right now. They're hiring across Research Engineer. Based in Remote, US.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% of all AI roles offer remote work.
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
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