AI/ML Engineer ðŸ§
Responsibilities– LLM configuration and optimization (Mistral, LLaMa, Qwen or others) – fine-tuning, quantization, performance tuning;– 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– 1+ years 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;– 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 A2-B1.Nice To Have– Hands-on experience with fine-tuning and dataset preparation/annotation;;– Experience with vector databases (Pinecone, Weaviate, FAISS);– Experience with Java.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.English: B1Experience: 1 yearWork location: RemoteOffice: Prague, CZWork type: Full-timeApply now