Senior Data Scientist, Workato
Control & execution platform for enterprise AI
Be an early applicant
Control & execution platform for enterprise AI
1001+ employees
Be an early applicant
1001+ employees
Company mission
To help businesses streamline their operations by providing a platform to automate their work and integrate their stacks, all in one place.
Role
Who you are
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or equivalent practical experience
- 3+ years of experience in Machine Learning Engineering, Data Science, or a similar role
- Strong Python programming skills
- Hands-on experience with NLP and/or LLM-based systems
- Strong understanding of software engineering fundamentals (testing, code quality, debugging, version control)
- Ability to work collaboratively in a fast-moving environment and drive projects with ownership
Desirable
- Experience with tool-use agents or workflow-aware AI systems
- Experience building AI products in enterprise SaaS environments
- Experience with A/B testing and statistical significance techniques
- Experience with LLMOps/MLOps tooling and practices (monitoring, evaluation pipelines, model rollout, CI/CD)
- Experience working with modern data warehouses such as Amazon Redshift Snowflake
What the job involves
- We are looking for an exceptional Middle / Senior Machine Learning Engineer / Data Scientist to join our growing AI team
- In this role, you will design, build, deploy, and improve ML/LLM-powered services and features that power intelligent automation and AI-driven product experiences across the Workato platform
- You will work closely with our Engineering, Product, and Design teams to define and track product metrics and evaluation strategies, design customer-facing experiments and dive deep to provide actionable insights
- This role is ideal for someone who combines strong ML/LLM intuition, software engineering skills and a practical mindset for shipping reliable, scalable AI systems
- Build and improve AI services using LLMs and custom machine learning models for production use cases
- Design, develop, and operate ML/LLM systems end-to-end, from prototyping to deployment and monitoring
- Write high-quality Python code that is testable, maintainable, and efficient
- Improve validation, observability, and performance monitoring for ML services (quality, latency, reliability, cost)
- Partner cross-functionally with product managers, platform engineers, and other stakeholders to ship AI-powered product capabilities
- Evaluate and improve existing implementations by identifying bottlenecks, bugs, and opportunities for optimization
- Design controlled experiments to test the features for our AI-based products and perform deep analysis from the results to find actionable insights
- Contribute to technical design and code reviews, helping raise engineering quality across the team
- Experiment and iterate on model behavior, prompting, retrieval, tool use, or orchestration strategies to improve user outcomes
Our take
Many businesses struggle with lack of team integration. There are a plethora of handy apps available, and various teams within businesses often use different processes, tools, and software. This has led to many businesses attempting to patch together technologies and create ad-hoc solutions that fail when they need to be scaled. Workato allows businesses to integrate data and apps so that teams can collaborate and communicate securely.
Workato has built a single platform that integrates apps, processes, data, and user experiences to improve efficiency, communication, and business flexibility. There are many integration platforms available, such as SnapLogic and Mulesoft Anypoint Platform, however, Workato has aimed its platform at users who have minimal technical experience, rather than the IT team.
Workato has continued to expand its partnerships and workforce, and is well set to see further growth as it innovates its product offerings and capabilities. The company was recognized as a Leader in the 2023 Gartner® Magic Quadrant™ for Integration Platform as a Service, making five years it has participated and five years it has been recognized.
Steph
Company Specialist at Welcome to the Jungle
Insights
-7% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Nov 2021
$200m
SERIES E
Sep 2021
$110m
SERIES D
Total funding: $415m
Company benefits
- Flexible Working Arrangements: We want to empower our employees to give us their 110%, and still be able to fully live their personal lives beyond what they do at Workato.
- Great Employee Benefits: Our employee benefits are designed not just to help everyone at Workato fulfill their basic and tangible needs, but also feel appreciated for their contributions to the company.
- Professional Development Opportunities: We are invested in the long-term professional development of our people, beyond what they bring to the table on their first day at work. We support individual career ambitions, and set aside training programs and budgets they can tap on to upgrade both soft and hard skills.
- Dedicated Wellness & Recreation Time: We make it a point to dedicate time to pause, recharge and get to know each other better. From virtual game nights to fitness sessions, there's always time for a little fun on the calendars.
Company HQ
Palo Alto, CA
Leadership
Vijay Tella
(Co-Founder & CEO)Spent 15 years as an Engineer at Teknekron and TIBCO, before joining Oracle as CSO. They also served as CEO at Qik, and VP at Skype.
Harish Shetty
(Co-Founder & Strategic Advisor)Previously held leadership roles in engineering at TIBCO, Blink, and iProfile.
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