Machine Learning Engineer [LLMs]

O projekcie: At deepsense.ai, you won’t just build AI solutions – you’ll shape how companies around the world use them. By joining us, you’ll: - Work with partners like OpenAI, NVIDIA, Anyscale, LangChain, Crusoe, and ElevenLabs. - Explore and apply the newest tech: LLMs & RAG, MLOps, Edge Solutions, Computer Vision, Predictive Analytics. - Tackle challenges in software & tech, pharma & healthcare, manufacturing, retail, telecoms & media. - Contribute to open-source projects – just take a look at our latest solution, ragbits, an agentic RAG framework with over 1.6k stars on GitHub. And the best part of working at deepsense.ai? - Spread your wings with clear career paths, technical or leadership. - Collaborate with 100+ AI experts with 15+ years of applied AI experience, as well as PhD-level researchers with academic backgrounds. - Tap into domain expertise and knowledge sharing whenever you need it. Wymagania: The ideal candidate: - Has 3+ years of experience in ML engineering and working with models in production environments. - Brings hands-on expertise with Large Language Models (LLMs) and Generative AI, including integration and inference optimization (latency, cost, scalability). - Is familiar with frameworks and tools for building and orchestrating LLM pipelines (LangChain, LlamaIndex, RAG, agent frameworks). - Can design and implement end-to-end ML/LLM pipelines, from data preparation and training/fine-tuning to production-grade APIs. - Has experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services (e.g., SageMaker, Vertex AI, Azure ML). - Has worked with SQL, NoSQL, and vector databases (Pinecone, FAISS, Weaviate). - Is fluent in Python and experienced with ML frameworks (PyTorch, TensorFlow, Hugging Face). - Knows how to deploy and monitor models (MLOps: CI/CD for models, logging, observability, quality monitoring). - Communicates clearly and can collaborate effectively with both Data Scientists and product/client teams. - Bonus: experience in prompt engineering and building simple AI user interfaces (Streamlit, Gradio). Codzienne zadania: - You’re closest to the models and AI itself, building ML/LLM pipelines, integrating, and optimizing models. - You have a background in deep learning, NLP, or CV, and today you’re hands-on with GenAI and LLMs. - You know techniques like fine-tuning, prompting, quantization, and LoRA and you understand how models work and how to adapt them for production. - You’ll dive into the hottest areas of AI: LLMs, agentic frameworks, RAG, inference optimization, and fine-tuning. - Projects aren’t just PoCs, the models you build go into production and reach real users. - You won’t be boxed into “just ML” you’ll collaborate with Data Scientists, Software Engineers, and MLOps to deliver end-to-end solutions.