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About the Role

We're hiring a Research Scientist to help build the vision-language models that turn Ironsite's data into the intelligence layer we're building. You'll work alongside our Chief Science Officer and research team on the training, benchmarking, and deployment of state-of-the-art VLMs that can interpret the complexity of a real construction site. Your work will run on data no other lab has, and your models will ship to jobsites where they actually change how things get built.

Responsibilities

Design, train, and iterate on vision-language models fine-tuned for spatial intelligence in construction environments.
Run experiments end to end, from data preparation through training, evaluation, and post-training.
Contribute to the frontier of what's possible on our data, whether that's establishing new baselines, improving post-training recipes, or exploring long-context architectures.
Contribute to our Construction Intelligence Benchmark suite across video question answering, temporal reasoning, activity recognition, and site-level analytical reasoning.
Design evaluation metrics that measure real-world construction task performance, not just standard academic benchmarks.
Own the evaluation loop for your own work so we always know what's actually improving.
Take your best models from research code to production deployment, working closely with our infrastructure and hardware teams.
Apply distillation, quantization, and model routing techniques so state-of-the-art understanding runs affordably across our growing fleet.
Learn from what happens in the field. Field data and production feedback should shape your next experiment.
Learn from senior researchers, contribute to the intellectual culture of the team, and start to develop your own point of view on what Ironsite's research should look like at scale.
Read papers, share ideas, and help set the technical bar for the whole team.

Requirements

2-4 years of hands-on research experience designing and training deep learning models, particularly transformer-based architectures.
Industry experience, top-tier PhD program, or equivalent.
Deep expertise with modern deep learning frameworks (PyTorch, JAX, or similar).
Strong proficiency in Python with solid software engineering fundamentals.
Experience working with large-scale vision or language datasets.
A track record of shipping meaningful research results, whether at a company, in a lab, or in publications.
A background in Computer Science, Machine Learning, AI, Robotics, or a related field.
Experience with vision-language models, video understanding, or multimodal architectures.
Hands-on experience with post-training techniques for large language or vision-language models (SFT, RL methods, parameter-efficient tuning such as LoRA).
Familiarity with the challenges of video data, including temporal reasoning and long-context modeling.
Publications at top-tier AI, ML, or CV conferences.

Skills

Deep learning models
Transformer-based architectures
PyTorch
JAX
Python
Software engineering
Large-scale vision datasets
Large-scale language datasets
Vision-language models
Video understanding
Multimodal architectures
Post-training techniques
SFT
RL methods
Parameter-efficient tuning
LoRA
Temporal reasoning
Long-context modeling

Location

San Francisco Bay Area

Work Type

On-site

Experience Level

2-4 years

Education Level

PhD program
Computer Science
Machine Learning
AI
Robotics
Related field

Salary/Compensations

$200k-$400k per year

Benefits

Significant early-stage equity
Full benefits including health, dental, vision, and 401(k) with 6% match
Access to dedicated GPU compute resources for research and experimentation
Daily catered breakfast and lunch

About the Company

Ironsite is building the intelligence layer for the physical world.
We design our own wearable hardware, deploy it alongside craft workers, and transform a shift's footage into a next-morning report.
Our internal team and purpose-built models label the data overnight and deliver actionable insights to superintendents by 5 AM.
We are accelerating the speed, efficiency, and predictability of construction, especially for complex, mission-critical infrastructure projects, including data centers, LNG facilities, sports stadiums, hospitals, and other large-scale developments, by training AI models on egocentric construction footage and labor productivity data.
We are built with a pro-worker philosophy at our core: we believe technology should empower the workforce, not replace it.
We're working to give craft workers and project leaders better visibility into what's happening on-site, while creating a system where the reality of construction and the chaos of each day is finally available to the people running the project.
Ironsite is deployed across several of the largest active construction projects in the country.
To date, we've captured more than 100,000 hours of construction footage across seven states, now process thousands of hours of site activity every day, and maintain a worker opt-out rate below two percent.
This is enabled by a workforce-first architecture that anonymizes devices, captures no audio, and never releases raw video.
Ironsite is backed by leading investors (8VC, South Park Commons, Saga Ventures) and prominent operators across technology and construction, including Eric Schmidt, Jeff Dean, Jeff Rothschild, Mark Leslie, Scott Wu, Eric Glyman, Karim Atiyeh, Russell Kaplan, and others, alongside over a dozen construction industry operators who have joined us as partners in building this.
Longer term, we believe Ironsite is the foundation for what construction becomes in the next decade.
We think the systems we're building are the operating system for how the physical world gets built, and will unlock a fundamentally different way of respect for our workforce.
One where craft workers are more valued, more visible, and better paid for the skill they bring, and where the industry finally has the intelligence layer that makes autonomous construction possible.
Both futures start with the same foundation.