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Job Type Administrative Salary Range $85,000 - $90,000 Start Date As soon as possible FLSA Status Exempt Application Deadline Jan 15, 2027 Contact Please submit an online application Job Description
Summary
Long Island University (LIU) and Fortune 50 company Dassault Systèmes have forged a groundbreaking partnership to establish the world’s first 3DEXPERIENCE Education and Research Center of Excellence in Life Sciences. This center is dedicated to advancing pharmaceutical sciences, precision medicine, and healthcare in the digital era through impactful research. It brings together a multidisciplinary team of experts from LIU, renowned for their collaborative spirit and expertise across diverse fields such as engineering, pharmacology, data management, clinical trial oversight, artificial intelligence, machine learning , and clinical research involving diverse populations and settings.
Key Responsibilities
- Define & implement the 3DEXPERIENCE Platform portfolio of offerings/apps and services.
- Manage the 3DEXPERIENCE Platform portfolio of offerings/apps and services.
- Work closely with students and faculty to ensure training on the various 3DEXPERIENCE Platform soft and hardware.
- Interface with Dassault Systèmes for any soft or hardware updates
Challenges Ahead
3DEXPERIENCE Platform Manager will:
- Focus on technical aspects of software product management.
- Lead and manage 3DEXPERIENCE Online Platform apps from the inception to the retirement in order to maximize 3DEXPERIENCE platform business values.
- Responsibilities span beyond project/app management and include the overall 3DEXPERIENCE dissemination strategy within students, faculty and state stakeholders.
- Use his/her rich experience of product development in discreet manufacturing industry, common customer needs/expectation and design processes, specifically related to the ongoing challenges, solutions, best practices and latest trends related to collaboration with the whole eco system, information creation and management.
- Will also use experience of software and social platforms, and SaaS trends on the market, to clearly define the product portfolio, capabilities, functionality, create and prioritize use cases and requirements.
- Analyze the market and work closely with the 3DEXPERIENCE end-users (companies for training and continuing education), in order to define and manage customer workflows and use cases to be used for gap definition and development prioritization.
- Will work closely with other teams and stake holders inside Dassault Systèmes in order to successfully plan, develop and deliver to market portfolio of Online CAD offerings. This include collaboration and synchronize activates with DS Platform Team, and all other brands (CATIA, BIOVIA, etc.), Product Definition, UX, R&D and QA teams.
Required Qualifications: This position offers excellent opportunities for technical career advancement and leadership by contributing to the development of algorithms and software in the aforementioned areas. The ideal candidate will have experience in simulation software development and proficiency in modern programming techniques. Additionally, a strong understanding of the following 3DEXPERIENCE Solutions is essential:
- 3DEXCITE – High Precision Rendering and Interactive Actions (AR / VR)
- BIOVIA – Molecular modeling • CATIA – Design Engineering and System Engineering
- CATIA - Architecture and Civil Engineering • DELMIA – Digital Manufacturing and Production
- ENOVIA – Collaborative Innovation and Project Management
- SIMULIA - Advanced Realistic Simulation
- SOLIDWORKS – 3D Designer for Product Design Candidates must have an earned a Master degree before the start date of the position in one of the following fields: Computational Sciences, Engineering, or a related field. Candidates with interest in research have the potential to prepare a PhD in the field of their choice enabling a career evolution as a faculty in LIU. The position will be housed in the Department of 3DS/FabLab/Accelerator facilities under the School of Engineering, AI and Computer Sciences.
Candidates must have an earned a Master degree before the start date of the position in one of the following fields: Computational Sciences, Engineering, or a related field. Candidates with interest in research have the potential to prepare a PhD in the field of their choice enabling a career evolution as a faculty in LIU. The position will be housed in the Department of 3DS/FabLab/Accelerator facilities under the School of Engineering, AI and Computer Sciences.
LIU is an equal opportunity employer. LIU is committed to extending equal opportunity in employment to all qualified candidates who can contribute to the diversity and excellence of our academic community. LIU encourages applications from all qualified individuals without regards to race, color, religion, genetic information, sexual orientation, gender and/or gender identity or expression, marital or parental status, national origin, ethnicity, citizenship status, veteran or military status, age, disability or any other basis protected by applicable local, state or federal laws. Hiring is contingent on eligibility to work in the United States.
Salary Context
This $85K-$90K range is in the lower quartile for Research Engineer roles in our dataset (median: $165K across 57 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 9,079 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Long Island University, 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 457 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($87K) sits 65% below the category median. Disclosed range: $85K to $90K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and AI Engineering Manager ($251,622). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Long Island University AI Hiring
Long Island University has 1 open AI role right now. They're hiring across Research Engineer. Based in Brooklyn, NY, US. Compensation range: $90K - $90K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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