Senior Machine Learning Engineer

The company unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. The company’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use the company to power world-class customer experiences every day.

Born from the Stanford AI Lab, the company has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. The company’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining the company to build the future of AI-driven customer experiences.

Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at the company.

About the role

Machine Learning Engineers at the company work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs.

Current focus areas include

• Agentic Assist: Lead and build next-generation agentic AI systems that augment contact center agents in real time. This track requires strong pre-LLM ML foundations, deep expertise in LLMs and modern prompting techniques, a rapid prototyping mindset, and a proven ability to translate cutting-edge research into scalable, production-grade systems.

• Agent & System Quality: Design evaluation frameworks and improve the reliability, robustness, and performance of LLM-powered agents. This includes diagnosing and mitigating failure modes such as hallucinations, retrieval errors, tool misuse, context drift, prompt brittleness, and multi-step reasoning breakdowns, while defining measurable quality metrics (e.g., accuracy, faithfulness, task completion, latency, and cost) for complex, non-deterministic systems.

• Insights: Architect and scale LLM and retrieval-augmented generation pipelines that ground models in enterprise data. This track focuses on building high-performance ML systems that process complex data, extract structured insights, and deliver real-time, actionable intelligence at scale.

Responsibilities

• Lead the design and development of the company’s next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches.

• Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.

• Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models.

• Improve reasoning, planning, and tool-use capabilities in real-world AI applications.

• Develop evaluation strategies for complex, non-deterministic systems, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies.

• Diagnose and mitigate real-world failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns.

• Define and measure quality metrics (e.g., accuracy, faithfulness, task completion, latency, cost, robustness) to improve system reliability and performance.

• Optimize AI systems for scalability, latency, security, and cost efficiency in production environments.

• Collaborate cross-functionally with product, frontend, and backend teams to integrate AI capabilities seamlessly into the company’s platform.

• Mentor engineers, contribute to technical strategy, and help shape the roadmap for the company’s AI systems.

Qualifications We Value

• Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s or Ph.D. preferred.

• 5–8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs.

• Strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems.

• Proven experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments.

• Experience building and evaluating complex agentic or multi-step LLM workflows.

• Strong knowledge of modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.

• Demonstrated ability to optimize real-time ML systems for performance, scalability, and reliability.

• Strong technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar.

Perks & Benefits

We offer a comprehensive and people-first benefits package to support you at work and in life:

• Comprehensive medical, dental, and vision coverage with plans to fit you and your family

• Flexible PTO to take the time you need, when you need it

• Paid parental leave for all new parents welcoming a new child

• Retirement savings plan to help you plan for the future

• Remote work setup budget to help you create a productive home office

• Monthly wellness and communication stipend to keep you connected and balanced

• In-office meal program and commuter benefits provided for onsite employees

Compensation at the company

The company’s approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table.

The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family.

Salary Range : $205,000–$270,000 + Offers Equity

Our use of AI in recruiting: We may use AI tools in our recruiting process, which require human review and oversight. If you have questions about our use of AI or wish to opt out, please contact [link for members] (if you are opting out, please use the subject ‘Opt-Out’ in your email).

Recording & AI transcription: We do not authorize candidates to record or use AI transcription of any interview by phone, notetaker app, AI glasses, or other device. Candidates may request an exception or accommodation for review during the interview process as needed.

Recruiting impersonation scams: We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All the company recruiting email communications will always come from the @the company .ai domain. Any outreach claiming to be from the company via other sources should be ignored.