AI/ML Senior Engineer at Itransition — NeverHard

Itransition has a new AI team that builds AI solutions for clients in any industry. Its projects range from adding AI to a system the client already runs to building a new product, and its work spans agents, assistants, and chat interfaces, as well as backend routing and optimisation, computer vision, and language model fine-tuning. As a Senior AI/ML Engineer, you will be one of the first engineers on the team. You will take a project from the client's request to a production feature and lead 2–3 engineers on the project. In this role, the hard part is usually the data and the client's process, not the model. A project phase may end with evidence that the data cannot support the feature. That is a valid result when it comes early and explains why. What is specific to this team: A new team: the first projects set how it works Direct contact with the client's managers and data A justified "this will not work" counts as a result, not a failure If you are close but not across all of it, apply anyway and say where you are unsure. Requirements Typically 5+ years in software or ML engineering; strong Python Knowing when a task needs AI and when plain code, a rule or a database query does it better LLM features and agents you took to production and kept running: function calling, RAG, agent workflows Agent frameworks: LangGraph, LlamaIndex or comparable Deployment to the cloud (Azure, AWS) and on premises, including local models Evaluation of LLM output: test sets agreed with the business, pass thresholds, error analysis Classical ML on tabular data: churn, segmentation, forecasting Planning the AI part of a project of 1 person-year or more, and leading 2–3 engineers on it Personal data and AI: GDPR, what may go to an external LLM provider and what may not Working English: you present results to the client's managers and defend a technical decision Not expected: depth in every kind of AI work. Depth in LLM applications is the core; the rest you pick up on projects. Responsibilities: Turn a client's request into a scope and an estimate: what data exists, what AI can do with it, what it costs Build a first version fast and check it on the client's real data Say early when the data cannot support a feature, and show why Take the feature to production and keep it running Lead 2–3 engineers and present results to the client's manager. We offer: Projects for such clients as PayPal, Wargaming, Xerox, Philips, adidas and Toyota Competitive compensation that depends on your qualification and skills Career development system with clear skill qualifications Flexible working hours aligned to your schedule Options to work remotely Corporate medical insurance covering services of private and public medical centers English courses online Corporate parties and events for employees and their children Gym membership compensation, corporate sport competitions (cybersport included) 5 days of paid sick leave per year with no obligation to submit a sick-leave certificate