About Workato: Workato is the only integration and automation platform that is as simple as it is powerful — and because it's built to power the largest enterprises, it is quite powerful. Simultaneously, it's a low-code/no-code platform. This empowers any user (dev/non-dev) to painlessly automate workflows across any apps and databases. We're proud to be named a leader by both Forrester and Gartner and trusted by 7,000+ of the world's top brands such as Box, Grab, Slack, and more. But what is most exciting is that this is only the beginning.Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care. That's why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. Also, feel free to check out why:Business Insider named us an "enterprise startup to bet your career on"Forbes' Cloud 100 recognized us as one of the top 100 private cloud companies in the worldDeloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North AmericaQuartz ranked us the #1 best company for remote workersResponsibilities: We are looking for a highly motivated and skilled Machine Learning Engineer to join our team at Workato. As a Machine Learning Engineer, you will be responsible for developing, deploying, and maintaining the machine learning models that power some of the world's most popular products and services. In this role, you will also be responsible for:Working with large datasets and developing data pipelines to ensure the accuracy and reliability of the models.Collaborating with cross-functional teams, including product managers, data scientists, software engineers, and designers to identify business requirements and design solutions that meet those requirements.Deploying and monitoring models in various environments, and continuously improving their performance and scalability.Staying up-to-date with the latest trends and technologies in machine learning, and contributing to the development of the company's machine learning infrastructure.Requirements:Qualifications / Experience / Technical Skills:Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.3+ years of experience in developing and deploying machine learning models in production environments.Strong programming skills in Python.Experience with machine learning frameworks such as TensorFlow, PyTorch.Experience with Langchain, Haystack, jsonformer, gorilla or llama_index is a plus.Experience with LLM such as Falcon, Pythia or LLaMa is a plus.Familiarity with big data technologies.Soft Skills / Personal Characteristics:Strong problem-solving skills and the ability to work independently and as part of a team.Excellent communication and collaboration skills.
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