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Mit Csail Jobs (NOW HIRING)

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 ...

Product Marketing Manager

New York, NY · On-site

$168K/yr

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 ...

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How much do mit csail jobs pay per hour?

As of Jul 21, 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.

What is CSAIL at MIT?

CSAIL (Computer Science and Artificial Intelligence Laboratory) at MIT is a leading research institute focused on computer science, artificial intelligence, and related fields. It conducts cutting-edge research, develops new technologies, and collaborates with industry and academia to advance computing innovations.

What is the difference between Mit Csail vs Data Scientist?

AspectMit CsailData Scientist
Required CredentialsAdvanced degrees in CS, AI, or related fields; research experienceBachelor's or Master's in CS, Statistics, or related fields; some research experience
Work EnvironmentResearch labs, academic settings, collaborative projectsCorporate offices, tech companies, data-driven environments
Employer & Industry UsageAcademic institutions, research centers, MIT-affiliated projectsTech firms, finance, healthcare, consulting
Common Search & ComparisonMit Csail vs Data ScientistData 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.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as healthcare professionals, software developers, and skilled tradespeople, are more likely to survive AI automation. These roles often involve nuanced decision-making, emotional intelligence, and hands-on skills that are difficult for AI to replicate. Continuous learning and adaptability remain important for job security in an evolving technological landscape.

Who is the head of CSAIL at MIT?

The head of CSAIL (Computer Science and Artificial Intelligence Laboratory) at MIT is the director, a position held by Professor Daniela Rus as of 2023. The director oversees research, administration, and strategic planning within the lab, which focuses on computer science and AI innovations.

What are the key skills and qualifications needed to thrive as an MIT CSAIL Researcher, and why are they important?

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.
More about Mit Csail jobs
What cities are hiring for Mit Csail jobs? Cities with the most Mit Csail job openings:
What states have the most Mit Csail jobs? States with the most job openings for Mit Csail jobs include:
Infographic showing various Mit Csail job openings in the United States as of July 2026, with employment types broken down into 1% Internship, 2% Full Time, 85% Part Time, 1% Temporary, and 11% Contract. Highlights an 21% Physical, 66% Hybrid, and 13% Remote job distribution, with an average salary of $43,104 per year, or $20.7 per hour.

AI Engineer: Computer Vision, LLMs & ML (Remote)

Intellus Build

San Francisco, CA • Remote

Full-time

Re-posted 6 days ago


Job description

Intellus Build Make Construction Intelligent

Work with ex-Narvar Founding CTO (Unicorn, $1B+). 6 AI patents. Enterprise AI pedigree: Google DCDE, Oracle, Macy's, Walmart Labs.

We're hiring founding team members to transform how the $12T global construction industry buildsfrom residential to mission-critical infrastructure.

AI Engineer: Computer Vision, LLMs & ML

Engineer the AI driving next-generation construction.

Location: Remote-US (San Francisco Bay Area Hybrid Preferred)

Type: Full-time

Compensation: Founding-team equity (12%) + base salary

Construction creates the world around usyet still runs on WhatsApp, spreadsheets, and gut feel. Sites generate terabytes of data dailyyet none of it tells anyone what to do next.

This isn't a data problem. It's an Intelligence problem.

We're building the nervous system for construction. Think Palantir meets Procore, but actually usable by contractors. Our first customers are already begging for access.

You'll be the founding AI engineer, building alongside our founder and construction industry veterans. Async-first. Remote-friendly. Zero bureaucracy. No meetings about meetings. Just ship code that moves dirt and dollars.

You'll turn cutting-edge LLM and vision research into tools that run on dusty job sites and mobile devices.

About the Role

Intellus Build is the Infrastructure of Truththe AI-native operating system that connects dirt to dollars.

The Problem: Construction sites generate terabytes of unstructured data dailyphotos, documents, videos, sensor readings. Currently, this valuable information goes to waste.

Your Mission: Build AI systems that transform construction chaos into actionable intelligence.

What You'll Build

As the founding AI engineer, you'll tackle problems that don't have Stack Overflow answers:

  • Build RAG systems that understand construction terminologyteach AI the difference between 'pour concrete' and 'poor concrete'
  • Deploy computer vision that detects safety violations from grainy phone photos taken at 6 AM
  • Create AI assistants that answer 'What's the status of the Stanford dorm project?' by reasoning across blueprints, contracts, RFIs, and daily photo logs
  • Design real-time progress tracking that works even when construction sites have terrible WiFi
  • Build domain-aware AI that makes construction sites safer and more efficient
  • Build verification systems that track equipment from PO to energization across complex supply chains
Requirements

You are:

  • 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
  • Comfortable with the full ML stack: data processing model selection deployment monitoring
  • Able to move quicklyyou prototype in hours, not weeks
Must Have
  • Shipped at least one LLM-based application used by real users
  • Experience with RAG, embeddings, and vector databases
  • Strong Python skills plus PyTorch, TensorFlow, or JAX
  • Ability to explain complex ML concepts to non-technical stakeholders
Nice to Have
  • Computer vision experience (YOLO, Segment Anything, etc.)
  • Published ML research or Kaggle competition medals
  • Experience with construction, manufacturing, or industrial datasets
  • Track record of optimizing inference costs
What You'll Work With

We're flexible on the stack, but likely:

  • LLM APIs: OpenAI, Anthropic, Geminimulti-model approach
  • Orchestration: LangChain, LlamaIndex, or custom frameworks
  • Vector stores: Pinecone, Weaviate, or pgvector
  • ML frameworks: PyTorch, TensorFlow, or JAX

You'll help shape these choices as we build.

Why This Role Matters
  • Real-world impact: Your models will help prevent workplace injuries and save lives
  • Unique datasets: Access to proprietary construction data that competitors don't have
  • Greenfield opportunity: Define the AI strategy from day one
  • Domain expertise: Work directly with construction industry veterans
  • Mission-critical scale: Your models will power verification for facilities where downtime isn't an option
  • Pedigree: A Stanford StartX company (elite sub-1% accelerator)
Ready to Build?

You'll complete two quick assessments to show us what you can do.

Top scorers get interviewed. We move fast. No bureaucracy.

Intellus Build is an equal opportunity employer. We welcome candidates from all backgrounds.