Manager, Data Science

<h1><strong>About Workato</strong></h1> <p>Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility.</p> <p>Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s fast-changing world. Learn how Workato helps businesses of all sizes achieve more at <a href="http://workato.com/" target="_blank">workato.com</a>.</p> <h1><strong>Why join us?</strong></h1> <p><span>Ultimately, Workato believes in fostering a </span><strong>flexible, trust-oriented culture that empowers everyone to take full ownership of their roles</strong><span>. We are driven by </span><strong>innovation </strong><span>and looking for</span><strong> team players </strong><span>who want to actively build our company. </span></p> <p><span>But, we also believe in </span><strong>balancing productivity with self-care</strong><span>. That’s why we offer all of our employees a vibrant and dynamic work environment </span><a href="http://www.workato.com/careers"><span>along with a multitude of benefits</span></a><span> they can enjoy inside and outside of their work lives. </span></p> <p><span>If this sounds right up your alley, please submit an application. We look forward to getting to know you!</span></p> <p><span>Also, feel free to check out why:</span></p> <ul> <li> <p><a href="https://www.businessinsider.com/47-enterprise-startups-to-bet-your-career-on-in-2020-2019-12"><span>Business Insider</span></a><span> named us an “enterprise startup to bet your career on”</span></p> </li> <li> <p><a href="https://www.forbes.com/cloud100/#a57477b5f941"><span>Forbes’ Cloud 100</span></a><span> recognized us as one of the top 100 private cloud companies in the world</span></p> </li> <li> <p><a href="https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/fast500-winners.html"><span>Deloitte Tech Fast 500</span></a><span> ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America</span></p> </li> <li> <p><a href="https://qz.com/work/2053446/the-best-companies-for-working-from-home/"><span>Quartz</span></a><span> ranked us the #1 best company for remote workers</span></p> </li> </ul><h1><strong>Responsibilities</strong></h1> <p>We are seeking an experienced <strong>Data Science / Machine Learning Engineering Lead</strong> to join our team and drive the development of advanced ML/AI capabilities. You will lead a team of Data Scientists / ML Engineers, focusing on building and deploying cutting-edge machine learning solutions using our modern ML infrastructure including Anthropic, OpenAI, and self-hosted LLMs.</p> <ul> <li> <p><strong>Team Leadership &amp; Management</strong></p> <ul> <li> <p>Lead, mentor, and develop a team Data Scientists, Data Engineers, ML Engineers</p> </li> <li> <p>Conduct regular 1:1s, performance reviews, and career development planning</p> </li> <li> <p>Foster a collaborative, innovative team culture focused on continuous learning</p> </li> <li> <p>Coordinate work allocation and ensure timely delivery of projects</p> </li> <li> <p>Facilitate knowledge sharing and best practices across the team</p> </li> </ul> </li> <li> <p><strong>Technical Leadership</strong></p> <ul> <li> <p>Design and implement scalable ML model training pipelines using modern toolset (e.g MLflow, Comet, Langfuse, WandB, Trino, dbt, Spark, Flink, etc)</p> </li> <li> <p>Lead fine-tuning initiatives for both commercial (Anthropic Claude, OpenAI GPT) and open-source LLMs</p> </li> <li> <p>Utilise self-hosted LLM infrastructure using Ray, AIBrix, and vLLM for optimal performance and cost efficiency with Lora/QLora </p> </li> <li> <p>Architect and oversee model continous validation frameworks within our ecosystem</p> </li> <li> <p>Develop real-time anomaly detection systems leveraging for streaming data processing</p> </li> <li> <p>Build predictive models for system performance, usage patterns, and automation workflow optimization</p> </li> <li> <p>Establish ML engineering best practices for model versioning, monitoring, and deployment on Kubernetes</p> </li> <li> <p>Creation of eval, validation and metrics pipelines for models during training and inference</p> </li> </ul> </li> <li> <p><strong>Strategic Initiatives</strong></p> <ul> <li> <p>Optimize the balance between commercial APIs (Anthropic, OpenAI) and self-hosted models for different use cases</p> </li> <li> <p>Partner with product and engineering teams to identify high-impact ML opportunities</p> </li> <li> <p>Define the team's technical roadmap aligned with company objectives</p> </li> <li> <p>Drive adoption of state-of-the-art ML techniques and tools</p> </li> <li> <p>Contribute to infra