About the Role
Applied AI Research Engineer, Early Stage Project
Location: Remote
Job Description:
Software Engineering
Remote-US
While this role is based out of Mountain View, CA, we do support remote hiring in Seattle, WA, Austin, TX, and New York, NY.
About the Team:
We are a team of engineers, scientists, and designers dedicated to making housing and development more sustainable and equitable. We are developing novel AI solutions to address complex challenges in these industries to drive greater equity, innovation and efficiency. Currently incubating at X, Alphabet’s innovation lab, we are now building the team that will scale our project for global impact. This is a rare opportunity to shape this early stage project in an extremely meaningful way.
About the role:
If you love developing AI approaches for challenging and unconventional applications, aren’t afraid to dive headfirst into new domains, and are motivated to have a major impact on an early stage project, then this could be a perfect fit for you.
We are looking for experienced Artificial Intelligence (AI) research engineers that have hands-on end-to-end experience spanning from data pipelining to modeling training to deployment. Experience with AI infrastructure, including serving model inference at scale, is a plus. We are looking for creative problem solvers who aren’t afraid to roll up their sleeves and build.
How you’ll make 10X impact:
- Develop cutting edge generative AI approaches for challenging 3D data types
- Create data pipelines, clean data, and generate synthetic datasets
- Train and validate models, using modern approaches including supervised fine tuning, retrieval augmented generation, parameter efficient fine-tuning, and more
- Deploy, monitor and iterate!
- Actively collaborate with cross-functional teams, domain experts, and end users to refine product needs and ensure impactful technology solutions.
What you should have:
- Ph.D. or Masters Degree in Computer Science, Machine Learning, or a related field or equivalent applied research experience.
- At least 3 years of industry experience in a software engineering role
- Deep understanding of ML pipelines, algorithms, and best practices for model development, deployment, and monitoring
- Strong background in deep learning concepts, architectures (e.g., Transformers, LLMs, GANs, etc.), and training techniques (e.g., Fine-tuning, self-supervised learning, transfer learning, etc.).
- Expertise and hands on experience with generative AI approaches: SFT, RAG, DPO, RLHF, etc.
- Experience in AI infrastructure: building scalable data pipelines, inference servers, monitoring services, and more
- Proven capacity to adapt to evolving AI research landscapes and contribute to the development and implementation of novel approaches.
- Experience applying ML/AI to real-world problems
- Passion for innovation and a willingness to experiment, learn quickly, and iterate based on data and feedback.
It’d be great if you also had these:
- Understanding of cloud platforms like GCP and infrastructure-as-code tools like Terraform.
- Prior experience in the real estate or with CAD-type data formats
- Startup experience where you’ve honed your ability to build, test, and learn rapidly.