ABOUT US - Voltai for founding AI Engineer We’re in stealth so there's not much public info about us You'll be working on novel, challenging, and difficult research & engineering problems at an exciting early stage startup out of Stanford that's working with one of the largest semiconductor companies in the world as a customer + backed by the best investors in Silicon Valley. Customers & Investors Our team is backed by Index Ventures, founders of Replit and VMWare, with partners who have worked at Palantir and Deepmind. Voltai is currently working with one of the largest semiconductor companies in the world, and has more customers in the pipeline. We're building at the intersection of two of the fastest-growing industries, semiconductors and AI. Our co-founder's backgrounds Priyanka Mathikshara , an Electrical Engineer, has worked on more than 200 devices that are currently in production. Her experience spans from contributing to Google’s hardware team to collaborating with NASA. Raised with a passion for electronics, she spent much of her youth aiding her father in his electronics venture and traveling to tech-hub Shenzhen, China. This combination of professional and personal experience has embedded a deep understanding of the hardware industry. Erfan Rostami is our AI maestro. He has been engaged in research at the renowned Stanford AI Lab (SAIL), a leading institute for AI development and research, under the guidance of Prof. Andrew Ng. His work as a framework engineer at Cerebras Systems has further honed his expertise, equipping him with the unique skill set needed to navigate the artificial intelligence landscape. Job description: We are on the hunt for A Founding AI Engineer with the vision and skill to develop and enhance our cutting AT systems. This pivotal role will challenge you to push boundaries of artificial intelligence, working on ambiguous projects such as fine tuning large language models, crafting sophisticated model evaluations, inventing novel search, retrieval and QA algorithms, orchestrating large networks of interconnected LLMs and ingeniously navigating the complexity of latency and model inference costs. Responsibilities: Develop and continuously improve our AI systems and approaches Execute fine tuning of large language models to optimize performance Conceive and conduct model evaluations to ensure efficacy and accuracy Create and implement innovative search, retrieval and QA algorithms tailored to user needs Design, build and assess sophisticated large scale systems of interconnected LLMs Address and overcome harsh engineering constraints such as latency issues and high costs of internal model inferences Ideal Candidate Traits A record of publications in top-tier AI conferences and competitions Experience gained with an elite AI-centric companies and research laboratories Demonstrate ability to transform research papers into production ready code A background in tackling intricate machine learning domains and issues Possession of an Electrical Engineering background is a plus Expertise with code generation models and applications Eagerness to embrace the "zero to one" mentality building from the ground up Strong foundations in Natural Language Processing, Reinforcement Learning Exemplary pedagogical skills, enhancing learning and collaboration A penchant for disruption and innovation, challenging traditional norms to uncover new insights Problem-solving mindset, relishing the opportunity to tackle complex, unprecedented challenges An optimistic attitude that energizes team morale and personal work ethic Resilience in the face of setbacks, maintaining momentum without loss of enthusiasm Proactive initiative, preferring to spearhead projects and learning through practical engagement 3 - 7 years of work experience, with a preference for candidates with startup exposure Training ML models in industry The selected candidate will have ample opportunity to apply their skills to real-world industry projects, ensuring their contributions have a significant impact on our operational success and technological advancements. Salary and Equity * Compensation: $180k - $350k * Equity: Competitive equity package Visa Sponsorship Exceptional candidates who require visa sponsorship to work in the US are encouraged to apply. Work Policy We offer flexibility with hybrid or remote working arrangements, albeit holding a strong preference for on-site collaboration. Our dynamic team thrives within the academic ambiance of Stanford's libraries and relishes our communal meals at campus cafes. While we welcome the energy of remote workspaces, we also cherish the synergy experienced when we unite in person. Employment Type This role is a full-time, W-2 position, integrating the candidate into our core team as a principal player.
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