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Junior ML/AI Engineer

Рівень:
junior
Джерело:
djinni.co
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We’re looking for an ML/AI Engineer with 1–2 years of experience to help develop, integrate, and improve machine learning and AI-powered solutions.

You’ll collaborate with experienced engineers and other team members to build practical AI applications, experiment with different approaches, and bring AI capabilities into real-world products.

What you’ll do

Develop and maintain AI/ML applications using Python

Work with machine learning libraries and frameworks to implement and evaluate models

Prepare, process, and analyze datasets for AI/ML tasks

Integrate LLM APIs and other AI services into applications

Experiment with prompts, model configurations, and different approaches to improve results

Contribute to the development of AI-powered features, including chatbots and intelligent automation

Work with embeddings, vector databases, and retrieval-based solutions when needed

Evaluate model outputs and help improve accuracy, relevance, and reliability

Write tests and maintain readable, reusable code

Collaborate with backend engineers, data engineers, and other stakeholders

Document experiments, technical decisions, and implementation details

What we’re looking for

1–2 years of commercial experience in AI/ML development, Python development with AI/ML responsibilities, or a related role

Good knowledge of Python and common development practices

Familiarity with libraries such as Pandas, NumPy, and scikit-learn

Understanding of fundamental machine learning concepts and model evaluation

Practical experience with at least one of the following: - LLM APIs and AI application development - Machine learning model development and evaluation - NLP or other applied AI solutions

Understanding of data preprocessing and basic statistical concepts

Familiarity with REST APIs, Git, and testing

Analytical thinking and the ability to investigate technical problems

Intermediate English or higher

Nice to have

Experience with OpenAI or other LLM APIs

Familiarity with RAG (Retrieval-Augmented Generation)

Experience with LangChain, LangGraph, or similar frameworks

Familiarity with vector databases such as Pinecone, Qdrant, or Weaviate

Experience with PyTorch or TensorFlow

Basic knowledge of embeddings, semantic search, and prompt engineering

Familiarity with Docker and cloud platforms such as AWS, Azure, or GCP

Understanding of AI evaluation, monitoring, and deployment practices

🎁 What we offer

100% remote work

Flexible working hours

Competitive compensation

Paid vacation and sick leave

Health insurance / medical support

Professional development and learning opportunities

A friendly, supportive team with direct communication

The opportunity to work on challenging international projects

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