Must have

• Python

• Machine learning

• Docker

• Kubernetes

• GenAI

• LLM

• AI

• Cloud platform

• Azure

• Azure ML

• SQL

• PyTorch

• TensorFlow

• English

• Polish

Nice to have

• NoSQL

• GCP

• User Interface

Requirements description

The ideal candidate:

• Has 4–5+ 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).

Offer description

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.

Your responsibilities

1. You’re closest to the models and AI itself, building ML/LLM pipelines, integrating, and optimizing models.
2. You have a background in deep learning, NLP, or CV, and today you’re hands-on with GenAI and LLMs.
3. You know techniques like fine-tuning, prompting, quantization, and LoRA and you understand how models work and how to adapt them for production.
4. You’ll dive into the hottest areas of AI: LLMs, agentic frameworks, RAG, inference optimization, and fine-tuning.
5. Projects aren’t just PoCs, the models you build go into production and reach real users.
6. You won’t be boxed into “just ML” you’ll collaborate with Data Scientists, Software Engineers, and MLOps to deliver end-to-end solutions.