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About Workato Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com 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. If this sounds right up your alley, please submit an application. We look forward to getting to know you! 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 world Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America Quartz ranked us the #1 best company for remote workers Responsibilities We are looking for an exceptional Mid / Senior Machine Learning Engineer / Data Scientist (OCR/CV) to join our growing AI team and work on OCR-focused product capabilities. You will design, build, deploy, and improve machine learning systems for intelligent document understanding. The project involves extracting information from complex document layouts, including tables, embedded images, multi-column text, forms, and other non-trivial visual elements, while maintaining high accuracy and robustness in production environments. This role is ideal for someone with strong analytical thinking, solid computer vision expertise, and hands-on experience building ML systems for real-world document understanding tasks. Experience with OCR pipelines and LLM-based post-processing or document understanding systems is highly desirable. In this role, you will also be responsible to: 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. Required Qualifications 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 CV and/or LLM-based systems . Experience deploying and operating ML services in production . 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. Preferred Qualifications 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 or Snowflake . Job Req ID: 2455
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
