Position Summary:
We are building cutting-edge AI systems—including large language models (LLMs), autonomous agents, and real-time AI services. Our team consists of builders, experimenters, and continuous learners working together to solve real-world problems using artificial intelligence. If you’re passionate about machine learning and ready to grow your career, you’ll fit right in.
Position Responsibilities:
As a Junior AI Engineer (1–2 years experience), you will contribute to designing, developing, and deploying AI-driven solutions. Your day-to-day work may include:
• Building AI-powered applications using LLMs, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP)
• Implementing capabilities such as function calling, agent orchestration, and tool integration
• Benchmarking AI models using LLM-as-a-Judge, few-shot evaluation methods, and automated testing pipelines
• Applying and experimenting with model optimization and quantization techniques
• Containerizing and deploying applications using Docker and Docker Compose
• Using Hugging Face Transformers for embeddings, tokenization, and text classification
• Working with vector databases for semantic search and retrieval
• Applying image processing and computer-vision techniques using OpenCV (segmentation, feature extraction, object detection)
• Fine-tuning deep learning and machine learning models
• Integrating applications with relational and non-relational databases (MariaDB, PostgreSQL, etc.)
• Working with queuing and task orchestration frameworks for background processing
Required Competencies:
Candidates with 1 to 2 years of hands-on experience in AI/ML engineering are preferred, with:
• Strong proficiency in Python
• Familiarity with PyTorch or TensorFlow
• Good understanding of core ML/NLP concepts, including LLMs and RAG workflows
• Experience working in Unix/Linux environments
• Exposure to asynchronous frameworks (FastAPI, asyncio, etc.)
• Comfort working with Docker and containerized environments
• Practical experience with Git and version control
Preferred Skills (Nice-to-Haves)
These are not mandatory but will strengthen your application:
• Understanding of quantization (GPTQ, AWQ, etc.)
• Experience using Hugging Face Transformers for NLP tasks
• Familiarity with vector databases like Qdrant or ChromaDB
• Experience with computer vision and OpenCV
• Exposure to databases (MariaDB, PostgreSQL, SQLite, etc.)
• Familiarity with queuing systems (RabbitMQ, Redis Queue, etc.)
• Understanding of MCP and agent orchestration tools (LangChain, LlamaIndex, Haystack, etc.)
What Matters Most
You don’t need to have mastered everything. We value curiosity, continuous learning, and a passion for building real AI products. If you are motivated, eager to experiment, and ready to grow in a hands-on environment, we encourage you to apply.
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