We use a management approach that is close to Agile. Among others, we use guided continuous improvement, task prioritisation, sprints, value delivery, and focus on commitment.

Agile Experience.

Abstract thinking.

like Notion, Slack, Zotero, Shortcut, Miro, Git.

Infrastructure Tools

A strong advantage would be

The company develops a system capable of semantic processing of programming code, e.g., code analysis, transformation, and synthesis, as well as operating a computational environment. The approach combines explicit knowledge representation in discrete structures with ML-assisted algorithms to manipulate those structures. The system we design should be able to follow the reasoning trajectory and examine the internal logic; identify a lack of information and interact with external sources; incorporate new knowledge at later stages equally inexpensive as at the initial ones.


Machine Learning / Data Science / Software Engineering

People tend to think that AI is solely Machine Learning, like ChatGPT (or DALL-E 2, or Microsoft Bing, or ChatSonic). We are building our solution on an alternative architecture which incorporates ML as a part.

Not just an ML

We put much effort into profound research and development of new underlying technologies rather than reusing existing ones. We like to explore unfairly neglected and non-conventional approaches to AI.

Going beyond

We want to be responsible in our research and development. We don't turn our noses up at AI safety research and take the issue of alignment seriously.

Safety and Alignment

That is, of course, a very basic condition. We want our colleagues to be healthy, happy and recreated.

Good Salary

Our team members work from both the office and homes all around the world. We are OK with that. However, we like to gather sometimes at the office to get on the same page.

Hybrid Remote

Outside scheduled team meetings, teammates are free to work on their tasks independently. When to work is a personal choice. Just do not overwork – that is inefficient.

Flexible Schedule

High autonomy is crucial for us – the small and agile team can achieve a breakthrough if its members are professional and independent. However, we promote helping each other. That is crucial too.

Autonomy

Automated code synthesis is a holy grail: many want it, but nobody has it. You can read more about it on the Company tab or just write to us. We love cross-pollination.

Challenging Work

What we value most are performance and results, not a strict process following. However, metrics, processes, and documentation are important too. We just keep their priorities low.

Low Bureaucracy

What we are offering

Running open-sourced models on our hardware.

Building pipeline for distributed training.

Integrating models with the rest of our systems.

Staying on top of architectures and frameworks.

Analysing and suggesting improvements for datasets.

In-depth knowledge of: Machine Learning, Deep Learning, Training customisation, ML frameworks.

Known architectures: Transformer, LLM, GNN, Autoencoders.

Bachelor’s degree or higher. English C1 or higher.

Who we are looking for

Make and fulfil commitments on time and at a high-quality level.

Commitment.

Ability to figure out how to do new tasks from adjacent specialisations.

All-Round.

Focus on the objective, looking for new approaches, fast forwarding orientation.

Startup Mindset.

Presenting own arguments, listening to others' arguments, developing the next steps to resolve the difficulty.