Location: San Francisco, CA, United States
Job Type: Full-time
Salary: $150K - $350K
Equity: 0.50% - 2.00%
Experience: 1+ years
Visa: Will sponsor
Skills: C++, Rust, Torch/PyTorch, Docker, CUDA, Transformers
Apply here: https://forms.gle/cSP7f2iy65efyKiq7
About Interfaze
At Interfaze, we're building a new model for deterministic developer tasks that expects high accuracy like OCR, web scraping, classification, STT, and more. We currently power thousands of systems in industries like healthcare, finance, government, SaaS and more which has processed billions of tokens every month.
We're hiring an AI Engineer & Researcher who is looking to push the boundaries of our models by implementing and experimenting with new research and techniques. As part of the Interfaze lab, you will help improve the performance and capabilities of our models by managing our AI lifecycle, including fine-tuning, automating data collection and cleaning, benchmarking, and deployment.
As a founding member at Interfaze, your role will be dynamic, offering opportunities to spearhead and launch innovative research, papers, and products into production while being the go-to expert for all things AI!
What you will do
Research and understand different machine learning techniques and papers, then experiment with real-world implementation
Experience with deep learning frameworks (e.g., TensorRT-LLM, PyTorch), and AI development tools is a must
Working closely with the team to train, deploy and serve models at scale on popular cloud providers like AWS, GCP, and more
Write papers on your research and experiments contributing to the growing open-source AI world
Writing detailed benchmarks on comparisons and analysis (e.g. comparing performance for two embedding models or benchmarking whisper 3 with another model)
Quantization and fine-tuning of LLMs and other models for our developer use cases
Optimizing models and GPU infra for cost-to-scale ratio based on load
Writing Python code and Jupyter Notebooks
Who you are
A strong AI Researcher with at least 5 years of experience, and paper publications at venues like ICML, NeurIPS, ACL, NAACL, and IEEE
Worked with most of our GPU infra and have a good understanding of our tech stack
Comfortable with working across the stack - model deployment, benchmarking, fine-tuning, monitoring, and scaling the service
Up-to-date with the latest papers, techniques, and experiments
Using AI to 100x your productivity
Natural curiosity to experiment with new concepts and tools while working closely with our community of developers
You care about building great products and love to geek out about the latest tech in AI
Open to feedback and have a growth mindset
Bonus if you
Enjoy working in a startup environment where you can take initiative and contribute to the zero-to-one phase of development
Previously ran a startup or worked as a founding team member in a startup
Benefits
Great compensation package and equity/shares
Flexible and remote-friendly
Annually run off-sites
Learn and Grow - we provide mentorship and send you to events that help you build your network and skills
Annual Education Allowance
Let's build benefits together
Process
Apply here: https://forms.gle/cSP7f2iy65efyKiq7
The entire process is fully remote and all communication will happen over email or via video chat.
Once you've submitted your application, the team will review your submission and may reach out for a short screening interview over a video call.
If you pass the screen you may be invited to complete a short task or discuss your past work.
If you pass the task/screen you will be invited to up to 2 follow-up interviews. The calls:
usually take between 20-45 minutes each depending on the interviewer.
are all 1:1.
will be with both founders, a member of either the growth or engineering team (depending on the role) and usually one other person from your immediate team or function.
Summary
Build and research AI models for deterministic developer tasks, including fine-tuning, benchmarking, quantization, deployment, and GPU optimization. Requires at least 5 years of AI research experience and publications at venues such as ICML or NeurIPS, plus hands-on work with PyTorch, CUDA, Docker, and cloud infrastructure.
Responsibilities
Research and implement ML techniques; train, deploy, and serve models at scale on cloud providers; write research papers and benchmarks; quantize and fine-tune LLMs; optimize models and GPU infrastructure; write Python code and Jupyter Notebooks
Qualifications
Strong AI researcher with at least 5 years of experience; publications at venues like ICML, NeurIPS, ACL, NAACL, and IEEE; GPU infrastructure and tech stack experience; comfortable across model deployment, benchmarking, fine-tuning, monitoring, and scaling
Experience requirements
At least 5 years of AI research experience; paper publications at venues like ICML, NeurIPS, ACL, NAACL, and IEEE; experience with GPU infrastructure and the tech stack; comfortable across model deployment, benchmarking, fine-tuning, monitoring, and scaling
Interview process
Fully remote process over email or video; application review; short screening interview; short task or past work discussion; up to 2 follow-up 1:1 interviews lasting 20-45 minutes
How to apply
Apply via Google Form; short screening interview; short task or past work discussion; up to 2 follow-up interviews
Benefits
Equity/shares; flexible and remote-friendly; annual off-sites; mentorship and events; annual education allowance