**Who are we?**
Safeguards is on a mission to unlock high-stakes AI for scalable impact. We're
well-funded by top VCs in San Francisco and working with top Fortune 500s.
We're working on novel models, new methods, and pushing cutting-edge research
to production around AI reliability and safety.
Founder is a former Data Scientist at BCG building Conversational AI solutions
for F500s and saw firsthand the challenges deploying LLMs. He holds his first
degree, an MSc from Oxford and attended Harvard as a postgrad doing AI
research at MGH.
**Who you are:**
* Proven track record of execution: You have 5+ years of engineering experience, including several years training and deploying world-class AI models
* You have hands-on production experience working with proprietary LLMs and fine-tuning open-source LLMs with HuggingFace, PEFT, RLHF, DPO, etc.
* Experience with evaluations and running hypothesis-driven experiments to benchmark the performance of LLM and RAG systems
* Publication record in ML conferences (ICML, NeurIPS, ICLR, CVPR) is a plus
**What We Offer:**
* Competitive compensation package (salary, equity, benefits) reflective of a founding member's contribution
* Unlimited growth opportunities to learn and grow into your own role, working on some of the most technically challenging problems of Generative AI
* A driver's seat to building with a world-class startup founder backed by top VCs
* Tuition reimbursement towards AI courses
Our startup recruits, employs, trains, compensates and promotes regardless of
race, religion, color, national origin, gender, disability, age, veteran
status, and other protected statuses as required by applicable law.
Our dedication to promoting diversity, multiculturalism, equity and inclusion
is more than a commitment - it is the foundation of what we do. And thus we
strongly encourage people from ALL backgrounds to apply for this position.
**Applicants must be authorized to work for ANY employer in the U.S. We are
unable to sponsor or take over sponsorship of an Employment Visa at this
time.**
