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.

Tasks

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

Requirements

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

Benefits

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!

#J-18808-Ljbffr

.img - itai's machine GmbH