5 days ago
Berlin, GermanySenior
Responsibilities
- Build and deploy ML-based software systems for advertising experiences and campaigns.
- Work with multimodal datasets including image, video, audio, text, and structured performance data.
- Contribute to Smartly’s MLOps and data platform and improve the productionization of AI/ML applications.
- Develop scalable data pipelines, evaluate and monitor models, and maintain services under SLA.
- Collaborate with product, engineering, infrastructure, colleagues, and customers to translate needs into viable solutions.
- Contribute to planning, retrospectives, knowledge sharing, pair programming, debugging, and broader team improvement.
- Stay current with generative AI, computer vision, natural language processing, and explainability.
Requirements
- 5+ years of experience developing and deploying production-quality software.
- 2+ years of experience delivering software services powered by machine learning.
- 2+ years of experience working with cloud infrastructure such as AWS or GCP.
- Fluency in Python; C++ or Java experience is a plus.
- Hands-on experience with PyTorch or TensorFlow and knowledge of MLOps tools such as MLflow or Kubeflow.
- Experience with feature engineering, model evaluation, diagnostics, monitoring, scalable ML data pipelines, and services maintained under SLA.
- A strong foundation in linear algebra, statistics, and calculus.
- Strong analytical, problem-solving, communication, adaptability, and architectural decision-making skills.
- A relevant M.Sc. is preferred.
- Strong written and verbal English communication skills.
Benefits
- Hybrid work arrangement requiring three office days per week, with remote work flexibility.
- Option to work abroad for up to 30 days annually.
- Healthcare packages, mental health services, paid holidays, and family leave.
- Equity options, performance-based rewards, competitive compensation, and career development opportunities.
- Inclusive global culture with diverse international teams and emphasis on trust, transparency, and open feedback.
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