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Hi there👋, I'm the founder of OrgOps. I’ve always been fascinated by the dynamics that shape organizations - the forces that bring people together, the constructive and disruptive elements that drive success or failure. My journey has led me to explore these phenomena deeply, and at OrgOps, I’m committed to redefining processes that empower teams to thrive.
My background spans over a decade in the tech industry, with leadership roles in both research and development. Currently, I lead a ML/DataOps team @ General Motors, where I focus on developing scalable software infrastructures to support production-level machine learning and deep learning models deployed in cloud environments. Previously, I served as Vice President of R&D at an Israeli startup, overseeing a multidisciplinary team of 20 developers, driving innovation in computer vision and natural language processing. My early career also includes roles as a data scientist, research assistant at Tel Aviv University, and data analyst for the Israel Defense Forces. Additionally, I served in a Israeli technological unit, which significantly shaped my approach to technology and leadership. I am also an active researcher with an international research group focused on climate technology. My contributions to academic research and publications further deepen my expertise in these fields.
I firmly believe that software development is a ritual - one that requires consistency, structure, and thoughtful design. Join me on this adventure as we redefine what makes a strong team, shape how tasks should be approached, and lead the way to a more effective continuous integration and delivery.
OrgOps is the perfect environment to learn, teach, and experience the development cycle as it should be - guided by expertise and driven by the collective knowledge of the group to achieve excellence.
My journey from Mechanical Engineering to Software Development - and now Data Science has been driven by a deep curiosity about how technology and people work together.
Over the years, I’ve learned that real growth in tech isn’t just about mastering code or systems; it’s about developing habits, processes, and ways of thinking that help teams thrive.
When I transitioned into software, I noticed a gap: the path for junior developers is often unstructured. Many talented minds face uncertainty, scattered learning, and a lack of meaningful feedback. I’ve been there - and that experience shaped my belief that learning to develop software should feel less like guesswork and more like craft.
At OrgOps, I help build that structure. Together, we focus not only on writing code but on developing the discipline, curiosity, and problem-solving mindset that make a great engineer. I see mentoring as a two-way process - a chance to explore how teams grow, how individuals build confidence, and how we can make learning both practical and fun.
If you’re looking to grow from junior to contributor - to turn curiosity into confidence - let’s make that journey together.
I'm Itay. I’m drawn to the full spectrum of the data world - from the algorithmic thinking that shapes insights to the operational systems that bring those insights to life. The most meaningful work, in my view, happens where these two domains meet.
My background combines academic research with hands-on engineering. I currently work as an ETL Developer at Optimove, focusing on building and maintaining the data pipelines that connect diverse client systems to our platform. Before that, I worked in the ML/DataOps domain at General Motors and later as a researcher applying causal inference and statistical methods to large-scale economic datasets. I am also completing an M.Sc. in Statistics, where my thesis explores deep network initialization failures.
Moving from a statistical background into engineering reshaped my understanding of what it means to be effective in this field. Strong mathematical intuition is important - but so are coding standards, data management practices, and real-world engineering fundamentals.
At OrgOps, I aim to help you build that practical foundation. Together, we’ll bridge the gap between theory and implementation and navigate the challenges of modern data operations and development.
Hi there! I’m Itzik. I’m an ML & Data Ops Engineer at General Motors. My day to day sits where real systems meet real models: Python-heavy engineering, data pipelines, CI/CD, Docker, Azure ML workflows, and the glue that turns ML work into something teams can ship, monitor, and maintain.
Over the last few years I’ve supported production computer-vision model integration around vehicles, which means living close to GPU infrastructure, training and evaluation pipelines, model KPIs, data/versioning hygiene, and the operational side of shipping updates safely.
I also work across roles - engineers, researchers, and data teams - to keep the full loop moving from data to training to deployment and back again.
What pulls me into OrgOps is the mission to close the gap between “knows the theory” and “can operate in production.” The idea is to move beyond passive learning into active simulation: a safe, realistic environment where engineers can practice tasks using the same kinds of tools and constraints they’ll face on the job. Think of it as a flight simulator for enterprise engineering - where readiness becomes something you can measure, not just assume.
As a mentor, I’m straightforward and hands-on. I’ll help you take fuzzy tasks and turn them into clean plans, debug methodically, structure code and pipelines so other people can actually live with them, and build credibility through outputs that can be verified - not just “I watched a course.”If you’re early in your journey (or switching into ML/DataOps) and you want direct guidance and honest feedback, let’s do it!