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 casesBuild custom ML models using TensorFlow, PyTorch, scikit-learn or similarConduct data preprocessing, feature engineering, and dataset augmentationOptimize models through hyperparameter tuning and architecture refinementApply MLOps best practices for model lifecycle managementConduct experiments and report on performance metricsSoftware Engineering
Write clean, maintainable, well-documented, and production-ready codeDevelop robust data pipelines for training and inferenceBuild RESTful / FastAPI-based APIs for model interactionCollaborate with backend, frontend, and product teams to integrate AI featuresImplement resilience patterns (error handling, retries, fallbacks)Ensure high code quality through testing, code reviews, and CI / CD workflowsCollaboration & Innovation
Work closely with product and engineering teams to define AI requirementsPartner with data scientists to operationalize research modelsStay up to date with the latest AI / ML / LLM research, frameworks, and toolsDocument architectural decisions, model design, and implementation detailsMentor junior engineers and guide best practices in ML engineeringRequirements
Technical Skills
Strong programming skills in Python (required)Experience with ML libraries : scikit-learn, pandas, NumPy, Hugging Face TransformersExperience 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 servicesFamiliarity with orchestration tools (Airflow, Kubeflow, Prefect)Experience implementing CI / CD for ML systemsNice to Have
Experience with LLM fine-tuning, embeddings, and prompt engineeringKnowledge 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 AutoMLPublications or contributions to open-source ML / AI projectsDegree in Computer Science, Mathematics, Engineering, or related fieldsSoft Skills
Strong problem-solving and analytical mindsetClear communication skills, including explaining technical concepts to non-technical stakeholdersAbility to work independently in a fast-paced environmentHigh attention to detail and commitment to code qualityPassion for AI, ML, LLMs, and emerging technologiesCollaborative mindset with interest in mentoring teammatesBenefits
Compensation package above industry standardsModern office at Berlin Alexanderplatz (free drinks, team events, bike garage)A culture built on trust, autonomy, and personal growthDirect influence on product and architecture decisionsWork on digital solutions with meaningful social impactHybrid work model : 4 days in the office / week + 1 month per year fully remoteAgile processes, flexible working models, and innovation-driven projectsWe are looking forward to your application!
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