MLE

What you will do

Planning application architecture using LLM (Large Language Model) as the core technology;

Developing ML backends and microservices to ensure functionality and integration of various services;

Building integration interactions with adjacent teams: active participation in meetings and solution coordination;

Optimizing current solutions with a focus on performance and load management (onnx, openvino, tensorrt).

What we expect from you

Experience as an MLE for 2+ years;

Experience developing classical machine learning models in NLP (Natural Language Processing) areas;

Solid knowledge of Python and experience in developing network/asynchronous applications;

Experience in developing, implementing, and evaluating the effectiveness of solutions based on modern NLP models as a lead or project leader;

Broad knowledge in the field of LLM, RAG (Retrieval-Augmented Generation), as well as experience in applying modern approaches to solution development;

Experience in building processes and implementing best practices in development and data analysis;

Knowledge of Docker, CI/CD, FastAPI, and SQL, with a readiness to develop solutions from scratch;

Experience with topic modeling, NER, clustering, SSL, few shot / unsupervised learning;

Experience participating in Gen AI solution implementation projects;

Experience in inference optimization (vllm, Triton Inference Server, similar).

What we offer

Work in Russia's largest integrated digital solutions provider;

Full or partial remote work from Russia is possible;

In Moscow - BC Akademik, winner of the Best "Class A Office Building. Moscow" project nomination. Opportunity to work from offices in Krasnodar and Novosibirsk.

Official employment - according to the Labor Code of the Russian Federation (full social package: annual paid leave of 28 calendar days, sick pay);

Official salary (base salary and annual bonus);

Benefits cafeteria from day 1: voluntary medical insurance, compensation for transport, internet, sports, training, etc.;

Corporate training: internal meetups, participation in conferences, access to corporate libraries of technical and business literature.