elasticsearch AWS Python Google BigQuery Google Cloud Platform Numpy Pandas Gitlab What you will do Design and develop innovative algorithms to power a personalized shopping experience, leveraging cutting-edge machine learning techniques Deploy your solutions into production, taking full ownership and ensuring high performance and scalability Combine your data science expertise with a pragmatic, agile approach to find innovative solutions and drive measurable results within a fast-paced environment Challenge the status quo by identifying areas for improvement in existing retrieval and reranking systems, particularly those relying heavily on business logic, and propose data-driven solutions Thrive in a dynamic, fast-paced environment with a flat hierarchy, where your ideas and contributions can make a real difference Who you are Proficiency in Python or experience with at least one scientific computing language (e.g., MATLAB, R, Julia, C++) Strong SQL skills with experience in analytical or transactional database environments Theoretical understanding of machine learning principles, coupled with a hands-on approach to building and iterating on models Proven experience in building and deploying machine learning solutions that deliver tangible business value Strong understanding of data structures, algorithms, and tools for efficiently handling large datasets (e.g. pandas, numpy, dask, arrow, polars, …) Experience designing, building, and managing data pipelines Familiarity with cloud-based model training and serving platforms (e.g., GCP Vertex AI, Amazon SageMaker) Solid understanding of statistical methods for model evaluation Big Data: Experience analyzing large datasets using statistical and machine learning techniques DevOps: Familiarity with CI/CD tools (e.g., GitLab CI/CD, Hashicorp Terraform) is a plus Generative AI: Experience with generative AI and agentic frameworks (e.g., LangChain, ADK, CrewAI, Pydantic AI, …) is a plus Understanding of recommendation, retrieval and reranking systems in e-commerce and retail is a plus Excellent written and verbal communication skills in English Ability to effectively communicate complex machine learning concepts to both technical and non-technical stakeholders Proven ability to collaborate effectively within a team to establish standards and best practices for deploying machine learning models A proactive approach to knowledge sharing and fostering a quick development environment Nice to have Experience with BigQuery Knowledge of time series and (graph) neural network models Familiarity with statistical testing and Gaussian Processes Strong Knowledge of Computer Vision libraries, (e.g. OpenCV, TensorFlow, PyTorch) Experience maintaining Machine Learning pipelines through MLOps frameworks (e.g.
Computer Futures sucht in Hamburg, Hannover, Berlin, Stuttgart, Köln, Düsseldorf, München, Frankfurt eine/n IT-Systemadministrator (m/w/d) (ID-Nummer: 13458481)
Develop and continuously enhance the OneCompiler toolchain, including the MLIR/IREE front end, intermediate representation (IR) transformations, and backend code generation Integrate compiler components into software products such as eIQ and ML SDKs Design optimization passes and hardware-specific lowering flows for efficient model execution Contribute to exploratory compiler initiatives such as training-graph ingestion, auto-tuning, heterogeneous scheduling, and runtime bindings Build and maintain model ingestion pipelines for PyTorch, ONNX, TensorFlow, and TFLite Collaborate closely with internal engineering teams and external partners to drive innovation across the compiler ecosystem Strong background in compiler design and modern ML compiler frameworks (e.g., MLIR/LLVM, TVM, IREE, XLA) Familiarity with model export workflows for PyTorch, ONNX, and TensorFlow Deep understanding of AI/ML models, quantization techniques, and hardware-aware optimizations Proficiency in C++ and Python, with experience implementing compiler passes or device backends Experience working with embedded or heterogeneous compute architectures (e.g., Cortex CPUs, NPUs, DSPs) Hands-on experience with IREE AOT compilation or its runtime is benefitical Experience developing new MLIR dialects is benefitical Fascinating, innovative environment in an international atmosphere Ihr Kontakt Referenznummer 860059/1 Kontakt aufnehmen Telefon:+ 49 621 1788-4297 E-Mail: positionen@hays.de Anstellungsart Freiberuflich für ein Projekt