AI/ML Senior Engineer

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