Junior+ ML Engineer

We are looking for a Junior+ Machine Learning Engineer to join our team and contribute to real-world ML projects. You will work on practical machine learning challenges, participate in model development and experimentation, and collaborate with experienced engineers to turn ideas into working solutions.

Our expectations:

• 1.5+ years of relevant experience in startups or professional services firms.

• Familiarity with software development and delivery processes and an understanding of their key stages.

• Knowledge of machine learning model development and tuning for tasks such as classification, regression, and clustering.

• Experience integrating off-the-shelf machine learning solutions.

• Experience working with large datasets and data processing systems.

• Ability to use data analysis to identify patterns and insights that help solve business problems.

• A solid mathematical background and knowledge of core machine learning algorithms and evaluation metrics.

• Experience deploying machine learning models to production.

• Knowledge of natural language processing (NLP) and large language models (LLMs).

• Experience developing agentic systems, including multi-tool and multi-agent solutions.

• Strong customer communication and negotiation skills.

• Ability to identify customer needs, gather and analyze requirements, and translate business requirements into technical specifications.

• Ability to define clear and achievable goals for machine learning tasks and projects.

• Ability to conduct customer demos and explain technical concepts and results clearly.

• English at B2 level and fluent Russian.

• Tech stack: Python, SQL, PostgreSQL, Pandas, FastAPI, Flask, Django, Pydantic, SQLAlchemy, scikit-learn, PyTorch, Transformers, Git, Bitbucket, CI/CD, Docker, OpenAI API, LangChain, LangGraph, LangSmith, Airflow, and BigQuery.

Responsibilities:

• Develop and implement machine learning algorithms.

• Move machine learning models from development into real-world applications.

• Compare different approaches to solving complex business problems.

• Collaborate with customers to identify their challenges and explore how machine learning can address them.

• Develop algorithms for recommendation and ranking systems.

• Build intelligent assistants.

• Keep models and language model instructions up to date.

It will be a plus:

• Experience in applying hyperparametric optimization techniques to improve model performance

• Ability to monitor models in production

• Experience in the full ML model delivery cycle: from data collection to delivery to production and continuing support; understanding of the technical background of deliveries