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.At AdvanceWorks we learn together, grow together, and have fun together. And we do all this while creating great software solutions for clients across many industries and geographies. We are constantly challenging ourselves and each other to use the latest technologies and the best methodologies, and make sure we walk the talk. What will be your role In this role you will integrate a technical team delivering great software that will help our clients to accomplish its business objectives by: Developing and implementing machine learning solutions, working directly with a prestigious client in the banking sector, and collaborating with technical teams to build and scale machine learning pipelines. Collaborating with data scientists to turn machine learning models into production services. Developing and maintaining robust and scalable web APIs to serve machine learning models. Contributing to the creation of frameworks that reuse technical solutions to known problems and promote solution sharing among projects and departments. Advocating for the adoption of frameworks that accelerate the resolution of machine learning problems at scale. Participating in the creation of machine learning pipelines, from data collection strategies to inference services building and deployment. Collaborating with DevOps, software architecture, and platform teams. Regularly contributing to the documentation of our systems and tools. Challenging feature requirements if you think they add no value. Participating and contributing to other company-wide initiatives. What should you bring to the team + 5 years of experience as a Machine Learning Engineer. Proficiency in at least one object-oriented programming language, such as C# or Java, and fluency in Python. Experience in common data science languages, such as Python or R, with excellence in at least one highly desirable. Knowledge of machine learning libraries, such as TensorFlow or Scikit-Learn. Clear understanding of the machine learning project lifecycle. Familiarity with streaming/messaging platforms, such as Kafka or RabbitMQ. Experience with data processing tools, such as Spark, Beam, and Flink, among others. Proficiency in at least one cloud platform, such as Azure, AWS, GCP, etc. Ability to use query languages, such as SQL, Spark SQL, etc., and experience with at least one NoSQL database, such as MongoDB, Redis, Cassandra, etc. Knowledge and experience in container technologies, such as Docker and Kubernetes. Experience in software build and release processes, unit testing, version control, etc., using Git. Advanced scripting skills and understanding of the Linux/Unix command line. Experience in automating infrastructure to train, evaluate, and deploy machine learning algorithms. Familiarity with Azure and many of its products (Databricks, CosmosDB, AKS, Azure DevOps). Experience with streaming platforms, with experience in Kafka being a plus. Knowledge of microservices architectures
