СШАResearch Engineer, Applied Research
1 нед. назад
СШАOnsite
applied researchmodelingvoice ai
Research Engineer role in applied research advancing AI agent models for customer-facing applications.
О компании
- is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia.
- We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do.
- Our co-founders are Bret Taylor and Clay Bavor . Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding , Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace.
- ’s Applied Research team advances the quality, speed, and cost efficiency of the models powering our agents across a wide range of tasks. Our work spans post-training open-weight models for specialized capabilities and pioneering new approaches to voice AI, turning research breakthroughs into reliable production systems.
- Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work.
- Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it.
- Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve.
- Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time.
- Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements.
Обязанности
- Tackle unsolved applied AI and ML problems. Pushing the boundaries of post-training, voice AI, and long-horizon task execution, building agents that can reason, adapt, and reliably carry out complex tasks for customers.
- Determine when to build specialized models and when to use externally provided frontier intelligence, balancing quality, speed, and cost to deliver customer value.
- Turn ambiguous product and customer problems into well-framed machine learning problems.
- Develop, fine-tune, evaluate, and deploy models that improve ’s customer-facing AI agents.
- Advance our post-training work, from supervised fine-tuning toward reinforcement learning and long-horizon optimization.
- Build rigorous evaluations that connect model performance to real-world agent quality.
- Work with large-scale, proprietary datasets spanning text and audio interactions.
- Collaborate across while taking ideas from experimentation through production deployment and customer impact.
Требования
- Strong experience building and deploying production machine learning and AI systems. We welcome backgrounds across applied ML, including search, ranking, recommendations, advertising, language, and speech.
- Excellent judgment in framing product problems as ML tasks and selecting the simplest & most effective approach.
- Experience working deeply with data, experimentation, evaluation, and model iteration.
- A practical, evidence-driven approach to ML, with strong judgement around when a problem calls for modeling and when a simpler solution will deliver the best outcome.
- The ability to operate with high agency and work across the stack when needed to deliver an outcome.
- Alignment with ’s values, including Craftsmanship, Customer Obsession, and Competitive Intensity.
- A degree in computer science, machine learning, or a related field, or equivalent professional experience.
Условия
- We want our benefits to reflect our values and offer the following to full-time employees:
- Flexible (unlimited) paid time off
- Medical, dental, and vision benefits for you and your family
- Life insurance and disability benefits
- Retirement plan dependent on country of employment
- Parental leave
- Fertility and family building benefits through Carrot
- Lunch, as well as delicious snacks and coffee to keep you energized
- Discretionary benefit stipend giving people the ability to spend where it matters most
- Free alphorn lessons
- These benefits are further detailed in 's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in 's equity plans subject to the terms of the applicable plans and policies.
Другое
- Experience with supervised fine-tuning or reinforcement learning.
- Experience in search, ranking, recommendations, or advertising systems.
- Experience training and deploying language, speech, or multimodal models.
- Experience designing model evaluations tied to real-world product outcomes.
- Experience working with large-scale consumer datasets or high-volume ML products.
- Contributions to applied ML research or benchmarks.
- We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.