Senior AI

We are looking for a Senior AI / Machine Learning Engineer to join our engineering team in Berlin, Germany. In this role, you will be responsible for integrating advanced AI models into production systems, building scalable ML pipelines, and training custom models that solve real business challenges.

You will combine strong software engineering skills with deep ML expertise to bridge the gap between research-driven models and scalable, production-ready AI solutions.

AI Model Integration & Deployment

• Integrate pre-trained AI/LLM models (OpenAI, Anthropic, Google, Hugging Face, etc.) into applications and backend services
• Design and implement APIs, microservices, and scalable model-serving architectures
• Optimize inference performance to improve speed, latency, and cost efficiency
• Build and maintain end-to-end ML pipelines for data processing and model deployment
• Implement observability tools (logging, monitoring, alerts) for AI systems in production

Model Training & Development

• Train, fine-tune, and evaluate machine learning models for specific use cases
• Build custom ML models using TensorFlow, PyTorch, scikit-learn or similar
• Conduct data preprocessing, feature engineering, and dataset augmentation
• Optimize models through hyperparameter tuning and architecture refinement
• Apply MLOps best practices for model lifecycle management
• Conduct experiments and report on performance metrics

Software Engineering

• Write clean, maintainable, well-documented, and production-ready code
• Develop robust data pipelines for training and inference
• Build RESTful / FastAPI-based APIs for model interaction
• Collaborate with backend, frontend, and product teams to integrate AI features
• Implement resilience patterns (error handling, retries, fallbacks)
• Ensure high code quality through testing, code reviews, and CI/CD workflows

Collaboration & Innovation

• Work closely with product and engineering teams to define AI requirements
• Partner with data scientists to operationalize research models
• Stay up to date with the latest AI/ML/LLM research, frameworks, and tools
• Document architectural decisions, model design, and implementation details
• Mentor junior engineers and guide best practices in ML engineering

Technical Skills

• Strong programming skills in Python (required)
• Experience with ML libraries: scikit-learn, pandas, NumPy, Hugging Face Transformers
• Experience with cloud environments (AWS, Azure, GCP)

AI Model Integration

• Experience integrating AI APIs (OpenAI, Anthropic Claude, Google AI, AWS Bedrock, etc.)
• Knowledge of deployment strategies (batch, streaming, real-time serving, edge)
• Hands-on experience with model-serving frameworks (TensorFlow Serving, TorchServe, ONNX, FastAPI)
• Proficiency in containerization (Docker, Kubernetes)

MLOps & Infrastructure

• Experience with experiment tracking tools (MLflow, Weights & Biases, Neptune)
• Understanding of cloud platforms (AWS, GCP, Azure) and their ML services
• Familiarity with orchestration tools (Airflow, Kubeflow, Prefect)
• Experience implementing CI/CD for ML systems

Nice to Have

• Experience with LLM fine-tuning, embeddings, and prompt engineering
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant)
• Experience with distributed training (multi-GPU, multi-node)
• Understanding of model optimization (quantization, pruning, distillation)
• Experience with reinforcement learning or AutoML
• Publications or contributions to open-source ML/AI projects
• Degree in Computer Science, Mathematics, Engineering, or related fields

Soft Skills

• Strong problem-solving and analytical mindset
• Clear communication skills, including explaining technical concepts to non-technical stakeholders
• Ability to work independently in a fast-paced environment
• High attention to detail and commitment to code quality
• Passion for AI, ML, LLMs, and emerging technologies
• Collaborative mindset with interest in mentoring teammates

• Compensation package above industry standards
• Modern office at Berlin Alexanderplatz (free drinks, team events, bike garage)
• A culture built on trust, autonomy, and personal growth
• Direct influence on product and architecture decisions
• Work on digital solutions with meaningful social impact
• Hybrid work model: 4 days in the office/week + 1 month per year fully remote
• Agile processes, flexible working models, and innovation-driven projects

We are looking forward to your application