AI/ML Engineer to $1900
Responsibilities:
- Configuring and optimizing Mistral 7B for business tasks (fine-tuning, quantization, performance optimization);
- Assessing required computational resources, selecting the optimal infrastructure for model deployment (on-premise or cloud), and analyzing cost efficiency;
- Implementing RAG to integrate models with vector databases;
- Orchestrating interactions between multiple ML services (e.g., one model generates tags, and another validates task descriptions).
- Developing a service for interacting with the model (API for predictions, model management, integration with our application).
- Optimizing model performance for real-world usage.
Requirements:
- Experience with LLM models (Mistral 7B, GPT-3/4, LLaMA, Claude, Falcon, Bloom, etc.);
- Understanding of Retrieval-Augmented Generation (RAG) and model integration with databases;
- Hands-on experience with fine-tuning and dataset preparation/annotation;
- Experience with vector databases (Pinecone, Weaviate, FAISS);
- Proficiency in Python and libraries like PyTorch, TensorFlow, Hugging Face, and LangChain;
- Experience in evaluating and optimizing infrastructure for AI deployments;
- Experience in developing APIs for integrating AI models into business processes;
- English level at least B1.
We offer:
- Regular result-based salary reviews;
- Comfortable working hours (10-19 Kyiv time zone);
- Bonus system;
- Established product-focused environment;
- Range of tasks, from quick and simple to challenging investigation to run;
- Cheerful & dynamic environment;
- Friendly and open-minded team;
- Virtual workspace with perspective to move into one of the offices;
- Mentorship;
- Attractive social package (unlimited and paid sick days, fully paid vacation, birthday day off, etc;)
- Sport and English classes discounts.
Hiring steps:
- First interview with the Recruiter;
- Technical interview with the Team Lead;
- Job Offer.
Required languages
English | B1 - Intermediate |
Python, Machine Learning, Mistral 7B, LLM, NLP, Deep Learning, RAG, Hugging Face, LangChain
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