Applied Machine Learning Engineer | GenAI / LLM / ML Systems

Aether Biomedical; Deutschland; Vor Ort; EUR 51.704 - 108.578; Vollzeit

Benefits dieser Stelle

Flexible work model

Zusammenfassung

Aether Biomedical is seeking an Applied Machine Learning Engineer to design and productionize AI systems. You will build ML models, work on LLM-based applications and deploy pipelines that train, evaluate and monitor models in real production environments.

Ideal candidates have strong Python, ML background and experience with PyTorch/TensorFlow, MLflow and fast APIs. This role offers a flexible remote/hybrid setup and multiple European offices.

Qualifikationen

• Strong experience with Python and ML frameworks.
• Hands-on ML/GenAI experience in production settings.
• Experience with real datasets and model deployment.

Aufgaben

• Design and build ML models for real product use cases.
• Develop LLM-based applications and AI agents.
• Create ML pipelines for training, evaluation, deployment and monitoring.
• Collaborate with engineers and product teams to ship features.
• Improve model accuracy, latency, and reliability in production.

Kenntnisse

Python

Machine Learning

Applied AI

PyTorch

TensorFlow

scikit-learn

ML pipelines

LLMs

API/backend

English (technical)

Tools

Docker

Kubernetes

MLflow

FastAPI

LangChain

OpenAI API

Jobbeschreibung

Applied Machine Learning EngineerGenAI / LLM / ML Systems / Production AI

Location: Remote / Hybrid

Offices: Warsaw, Kraków, Wrocław, Gdańsk

Employment type: B2B or Employment Contract

Seniority: Mid+ / Senior

Recruitment process: Remote

Salary range: B2B: 26 000 - 42 000 PLN net + VAT; Employment Contract: 20 000 - 32 000 PLN gross

About the project

Our client is developing advanced AI-powered products where Machine Learning is not an internal experiment, but a core part of the product experience. The team is building systems that use modern ML and GenAI techniques to understand data, support decision-making, automate complex workflows, generate insights, personalize user experiences and improve business processes.

What you will work on

• Designing, building and improving Machine Learning models for real product use cases


• Working on LLM-based applications, RAG pipelines, embeddings, semantic search or AI agents


• Developing ML pipelines for training, evaluation, deployment and monitoring


• Building features based on structured and unstructured data


• Preparing datasets, improving data quality and designing features


• Evaluating model performance using offline and online metrics


• Improving accuracy, reliability, latency, cost and stability of AI systems


• Deploying models and ML services into production environments


• Collaborating with software engineers, data engineers, product teams and business stakeholders


• Experimenting with new AI approaches and translating them into practical product features


• Building systems that can learn from feedback and improve over time

What we are looking for

We are looking for someone with:

• Strong experience with Python


• Practical experience in Machine Learning or Applied AI


• Experience with frameworks such as PyTorch, TensorFlow, scikit-learn or similar


• Good understanding of model training, validation, evaluation and deployment


• Experience working with real datasets and production-oriented ML problems


• Ability to write clean, maintainable and testable code


• Good understanding of data processing, feature engineering and model performance metrics


• Experience with APIs, backend services or ML model serving


• Ability to work closely with product and engineering teams


• Good problem-solving skills and ownership mindset


• English allowing you to work in an international technical environment

Nice to have

It would be great if you also have experience with:

• LLMs, GenAI or NLP systems


• RAG, vector databases, embeddings or semantic search


• LangChain, LangGraph, LlamaIndex, OpenAI API, Anthropic API or similar tools


• Fine-tuning, prompt engineering, model evaluation or guardrails


• MLOps tools such as MLflow, Weights & Biases, Airflow, Kubeflow or similar


• Cloud platforms such as AWS, GCP or Azure


• Docker, Kubernetes or CI/CD


• Model serving with FastAPI, BentoML, TorchServe, Triton or similar


• Data warehouses, data lakes or modern data platforms


• Recommendation systems, ranking models, forecasting, classification or anomaly detection


• A/B testing, experimentation or production monitoring

Technical stack

• Core: Python, Machine Learning, PyTorch/TensorFlow/scikit-learn, SQL, APIs, data processing


• Nice to have: LLMs, RAG, embeddings, vector databases, LangChain/LangGraph, MLflow, Docker, Kubernetes, AWS/GCP/Azure, FastAPI

What the client offers

• Work on modern AI and Machine Learning products


• Opportunity to build production-grade AI systems, not only experiments


• Projects involving GenAI, LLMs, ML systems, data and product intelligence


• Strong technical team and space for ownership


• Flexible work model: fully remote or hybrid


• Offices in Warsaw, Kraków, Wrocław and Gdańsk


• Fast and transparent recruitment process


• B2B or Employment Contract


• Attractive salary depending on experience


• Opportunity to grow in one of the fastest-growing areas of engineering