About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Recent graduate from top AI program (Stanford AI Lab, MIT CSAIL, or equivalent) OR 23+ years building production ML systems * Focused on practical AI applications, not just research demos
Quick apply
Recent graduate from top AI program (Stanford AI Lab, MIT CSAIL, or equivalent) OR 23+ years building production ML systems * Focused on practical AI applications, not just research demos
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Product Manager
San Francisco, CA · On-site
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Product Manager
San Francisco, CA · On-site
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Product Manager
San Francisco, CA · On-site
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Product Manager
San Francisco, CA · On-site
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Account Executive
San Francisco, CA · On-site +1
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Account Executive
San Francisco, CA · On-site +1
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Solutions Architect
San Francisco, CA · On-site
$74.25 - $97.75/hr
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Solutions Architect
San Francisco, CA · On-site
$74.25 - $97.75/hr
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Solutions Architect
San Francisco, CA · On-site
$120 - $160/hr
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
Solutions Architect
San Francisco, CA · On-site
$120 - $160/hr
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency ...
DATA ANALYST, SRS, COMPUTATIONAL BIOLOGIST, Computer Science and Artificial Intelligence Laboratory (CSAIL) -Computational Biology Group, to work at the interface of computational and experimental ...
DATA ANALYST, SRS, COMPUTATIONAL BIOLOGIST, Computer Science and Artificial Intelligence Laboratory (CSAIL) -Computational Biology Group, to work at the interface of computational and experimental ...
SENIOR RESEARCH ADMINISTRATOR , Computer Science and Artificial Intelligence Lab , will serve as a member of CSAIL Headquarters; perform comprehensive pre- and post-award financial research ...
SENIOR RESEARCH ADMINISTRATOR , Computer Science and Artificial Intelligence Lab , will serve as a member of CSAIL Headquarters; perform comprehensive pre- and post-award financial research ...
Mit Csail information
See salary details
$11.06 - $12.48
0% of jobs
$12.48 - $13.90
0% of jobs
$13.90 - $15.32
1% of jobs
$15.32 - $16.74
1% of jobs
$16.74 - $18.16
13% of jobs
$18.76 is the 25th percentile. Wages below this are outliers.
$18.16 - $19.58
24% of jobs
The median wage is $20.20 / hr.
$19.58 - $21
25% of jobs
$22.04 is the 75th percentile. Wages above this are outliers.
$21 - $22.42
15% of jobs
$22.42 - $23.84
9% of jobs
$23.84 - $25.26
6% of jobs
$25.26 - $26.68
5% of jobs
$11
$20
$26
How much do mit csail jobs pay per hour?
As of Aug 11, 2026, the average hourly pay for mit csail in the United States is $20.72, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $22.36 per hour, depending on experience, location, and employer.
What is MIT CSAIL?
MIT CSAIL stands for the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory. It is a leading research institute that focuses on computer science, artificial intelligence, robotics, and related fields. CSAIL is known for its groundbreaking research and has contributed to advances in computing, machine learning, cybersecurity, and more. The lab brings together faculty, students, and industry partners to solve complex technological challenges and push the boundaries of what computers can do.
What types of interdisciplinary collaborations can researchers expect when working at MIT CSAIL?
At MIT CSAIL, researchers frequently collaborate across diverse fields such as computer science, artificial intelligence, robotics, biology, and data science. The lab encourages teamwork both within CSAIL and with other MIT departments, fostering a vibrant environment for groundbreaking research. This interdisciplinary approach not only broadens individual skill sets but also opens doors to innovative projects and impactful advancements. Researchers often work in teams comprising faculty, students, and industry partners, providing ample learning and networking opportunities.
How do I get into MIT Csail?
To work at MIT CSAIL, candidates typically need a strong background in computer science, artificial intelligence, or related fields, often demonstrated through relevant degrees, research experience, or technical skills. Hiring processes may include submitting a detailed application, providing references, and participating in interviews or technical assessments. Familiarity with programming languages and research tools is also beneficial.
What is the difference between Mit Csail vs Data Scientist?
| Aspect | Mit Csail | Data Scientist |
|---|---|---|
| Required Credentials | Advanced degrees in CS, AI, or related fields; research experience | Bachelor's or Master's in CS, Statistics, or related fields; some research experience |
| Work Environment | Research labs, academic settings, collaborative projects | Corporate offices, tech companies, data-driven environments |
| Employer & Industry Usage | Academic institutions, research centers, MIT-affiliated projects | Tech firms, finance, healthcare, consulting |
| Common Search & Comparison | Mit Csail vs Data Scientist | Data Scientist roles, careers, salaries |
Mit Csail primarily involves research and development in AI and computer science within academic and research settings, often requiring advanced degrees. Data Scientists focus on analyzing data to inform business decisions, working mainly in industry. While both roles involve data and AI, Mit Csail emphasizes research, whereas Data Scientists focus on practical data application in business environments.
What are the key skills and qualifications needed to thrive as an MIT CSAIL researcher?
To thrive as an MIT CSAIL Researcher, you need a strong background in computer science, mathematics, and research methodologies, often supported by an advanced degree such as a PhD. Familiarity with programming languages (e.g., Python, C++), machine learning frameworks, and academic publishing systems is essential. Critical thinking, creativity, and strong collaboration skills help researchers innovate and work effectively within multidisciplinary teams. These abilities are crucial for advancing computational research and contributing impactful solutions to complex scientific problems.
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Full-time
Medical, Dental, Vision, Retirement, PTO
Re-posted 22 days ago
Job description
About Liquid AI
Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.
The Opportunity
The VLM team builds vision-language models that run on-device, under tight latency and memory constraints, without sacrificing quality. We have released four best-in-class models and we're just getting started.
This team owns the full VLM pipeline end-to-end: from researching new architectures and training algorithms through data curation, evaluation, and deployment. You'll join a focused, hands-on group that works directly on models and collaborates closely with our pretraining, post-training, and infrastructure teams. Success here is measured by the capability of the models we ship.
Minimal qualifications:
This role is for you if you have experience in some of the following:
What working here might look like:
What Success Looks Like (Year One):
What We Offer:
Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.
The Opportunity
The VLM team builds vision-language models that run on-device, under tight latency and memory constraints, without sacrificing quality. We have released four best-in-class models and we're just getting started.
This team owns the full VLM pipeline end-to-end: from researching new architectures and training algorithms through data curation, evaluation, and deployment. You'll join a focused, hands-on group that works directly on models and collaborates closely with our pretraining, post-training, and infrastructure teams. Success here is measured by the capability of the models we ship.
Minimal qualifications:
- Hands-on experience in training or evaluating VLMs with demonstrated experimental rigor.
- Ability to turn research ideas into scalable implementations, refine and iterate through hypotheses.
- Proficiency in Python and at least one deep learning framework.
- M.S. or Ph.D. in Computer Science, Mathematics, or a related field; or equivalent industry experience.
This role is for you if you have experience in some of the following:
- Building or optimizing multimodal training or data pipelines.
- Experience with distributed training (DeepSpeed, FSDP, Megatron-LM, etc.).
- Multimodal post-training experience (SFT, preference optimization, RL-style methods).
- Dataset design and data quality expertise (quality and diversity assessment, long-tail mining).
- Prior open-source contributions (code, data, models) on GitHub or Hugging Face.
- Published research at top AI conferences (NeurIPS, ICML, CVPR, ECCV, ICLR, ACL, etc.).
- Experience with computer vision or visual representation learning.
What working here might look like:
- Lead a new model capability end-to-end from task spec through data curation, training recipe, ablations, evaluation, and into the final shipped model.
- Improve visual reasoning through reinforcement learning and preference optimization methods.
- Push the quality-efficiency frontier on token efficiency via encoder/connector design. Exemplary outcome: a connector that cuts vision tokens without quality loss.
What Success Looks Like (Year One):
- The VLM models we ship are state-of-the-art.
- You own a major work-stream (for instance, video understanding, preference data quality, or encoder architecture) end-to-end.
- At least one model has shipped to production with your direct contribution.
What We Offer:
- Full ownership: You own your work from architecture to deployment.
- Compensation: Competitive base salary with equity in a unicorn-stage company
- Health: We pay 100% of medical, dental, and vision premiums for employees and dependents
- Financial: 401(k) matching up to 4% of base pay
- Time Off: Unlimited PTO plus company-wide Refill Days throughout the year
About Liquid AI
Sourced by ZipRecruiter
Industry
Library and information services
Company size
11 - 50 Employees
Headquarters location
Cambridge, MA, US
Year founded
2023