AI Research/Machine Learning Engineer - Agent Products (Palo Alto)

Qualifications

• Proven research experience with large-scale LLMs and Deep Learning systems
• Strong Post-Training skills, with a familiarity with both supervised and reinforcement learning techniques, including reward formulation, a good sense for evaluation, etc
• A strong consumer product intuition especially for Agent products, with a willingness to unblock one-self at any level of the stack, and take ownership of the end-product experience
• Understands how to make tradeoffs in developing an end-to-end agent, including training technique, model architecture, prompting, etc
• Minimum of 5 years of working on relevant deep learning research areas
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Benefits

• The cash compensation range for this role is $200,000 - $280,000
• Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above
• Equity: In addition to the base salary, equity may be part of the total compensation package
• Benefits: Comprehensive health, dental, and vision insurance for you and your dependents
• Includes a 401(k) plan

Responsibilities

• Design a production and training system that allows for an autonomous LLM-powered agent performs various tools across web, browsing, retrieval, code execution in order to answer a user’s open-ended prompt / query and returns a high quality answer with citations
• Partner with the Core Research & Post-Training Team to refine the expansion, reformulation, querying, and summarization of our models against Perplexity’s retrieval index
• Improving the speed and quality of our codebase and engineering processes to ensure we consistently deliver an amazing product experience
• Collaborating with Perplexity GTM leaders as well as a wide breadth of stakeholders (e.g
• to develop integrated product solutions that span across a wide breadth of research verticals like Travel, Retail, etc

Full Description

Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world’s leading AI platforms. Perplexity has raised over $1B in venture investment from some of the world’s most visionary and successful leaders, including Elad Gill, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, Nvidia, Samsung, and many more. Our objective is to build accurate, trustworthy AI thatpowers decision-making for people and assistive AI wherever decisions are being made. Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month–a number that’s growing rapidly for one simple reason: everyone can be curious.

Responsibilities

• Design a production and training system that allows for an autonomous LLM-powered agent performs various tools across web, browsing, retrieval, code execution in order to answer a user’s open-ended prompt / query and returns a high quality answer with citations.

• Partner with the Core Research & Post-Training Team to refine the expansion, reformulation, querying, and summarization of our models against Perplexity’s retrieval index.

• Improving the speed and quality of our codebase and engineering processes to ensure we consistently deliver an amazing product experience.

• Collaborating with Perplexity GTM leaders as well as a wide breadth of stakeholders (e.g. Motorola, TripAdvisor, etc.) to develop integrated product solutions that span across a wide breadth of research verticals like Travel, Retail, etc.

Qualifications

• Proven research experience with large-scale LLMs and Deep Learning systems.

• Strong Post-Training skills, with a familiarity with both supervised and reinforcement learning techniques, including reward formulation, a good sense for evaluation, etc.

• A strong consumer product intuition especially for Agent products, with a willingness to unblock one-self at any level of the stack, and take ownership of the end-product experience.

• Understands how to make tradeoffs in developing an end-to-end agent, including training technique, model architecture, prompting, etc.

• Minimum of 5 years of working on relevant deep learning research areas.

The cash compensation range for this role is $200,000 - $280,000.

Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above.

Equity: In addition to the base salary, equity may be part of the total compensation package.

Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.

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