Senior Machine Learning

Responsibilities:

• Implement end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, model retraining, model deployment and metadata tracking
• Identify new opportunities to improve business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset
• Work with data scientists and analysts to create and deploy new product features on the ecommerce website, in-store portals and mobile app
• Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation
• Write efficient and scalable software to ship products in an iterative, continual-release environment
• Contribute to and promote good software engineering practices across the team and build cloud native software for ML pipelines
• Contribute to and re-use community best practices
• Embody the values and passions with empathy to engage with colleagues from multiple backgrounds

Requirements:

• University or advanced degree in engineering, computer science, mathematics, or a related field
• 7+ years experience developing and deploying machine learning systems into production
• Experience working with a variety of relational SQL and NoSQL databases
• Experience working with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with at least one cloud provider solution (AWS, GCP, Azure) and understanding of severless code development
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Previous experience developing predictive models in a production environment, MLOps and model integration into larger scale applications
• Experience with Machine and Deep Learning libraries such as Scikit-learn, XGBoost, MXNet, TensorFlow or PyTorch
• Exposition to GenAI and solid understanding of multimodal AI via HuggingFace, Llama, VertexAI, AWS Bedrock or GPT
• Knowledge of data pipeline and workflow management tools
• Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation
• Working experience with native ML orchestration systems such as Kubeflow, Step Functions, MLflow, Airflow, TFX
• English level: B2, C1
• Relevant working experience with Docker and Kubernetes is a big plus

Offer:

• Private medical care
• Co-financing for the sport card
• Training & learning opportunities
• Constant support of dedicated consultant
• Team-building events organized by DCG
• Employee referral program