DevOps/ML Engineer (m/f/d)
At Machine Learning Reply, we work with our customers on cutting-edge projects for which we are looking for DevOps and ML Engineers to support our customer projects around machine learning and data processing across various industries. To expand our team, we are looking for a talented and highly skilled consultant with a technical background to join our team. As a consultant, you will be responsible for providing expert advice and technical support to our clients.
If you're a DevOps or ML Engineer or just starting out in the field of machine learning and/or DevOps engineering - if you never lose focus, love coding, data and AI, and are passionate about bringing your ideas to life - then we want to hear from you!
Responsibilities:
Design innovative, technical approaches for data intensive and applications with a focus on machine learning and artificial intelligence.
Implement and take ownership for your solutions on in either cloud based (AWS, Azure or GCP) and/or on-premises infrastructures of our customers.
Automate recurring tasks by state-of-the-art DevOps and MLOps concepts, enabling your customers to significantly reduce their time-to-delivery.
Take care of the necessary monitoring, failover, and recovery infrastructures that allow our customers save operation of their machine learning solutions in agreement with latest regulatory requirements
Closely interact with customers and stakeholders to translate concrete and complex business requirements into production-ready solutions
Collaborate with various disciplines such as enterprise architects, analysts, data scientists or data engineers to develop data-intensive applications such as data warehouses, data lakes and/or data platforms
What we offer you:
Access to work on projects across industries (large and mid-market companies in Banking, Insurance, Automotive, Retail, etc.)
Broaden your skills through interdisciplinary work and training in the areas of data engineering, cloud architecture, and data science
Benefit from industry-leading cooperations in the cloud, BI, and AutoML field
Very active social program - including training, conferences, team buildings, Reply Exchange, communities of practices, and hackathons
Work in an open, flat environment, within a broad Reply knowledge-sharing network
Award-winning office space in downtown Munich with access to “Stammstrecke”
You choose your state-of-the-art equipment
Public transport ticket with Deutschlandticket
Gym-membership subsidy for a gym of your choice
Flexible work environment between client, Reply office, and remote work
Minimum Job Requirements / Qualifications:
Bachelor’s / master’s degree in computer science or any other related fileds (e.g. engineering, statistics, physics).
First practical experience with DevOps/MLOps principals and computing platforms like Microsoft Azure, AWS and GCP as well as Databricks.
Ability to convincingly communicate and present analytical results to management.
We cover the full lifecycle of Data, from Cloud Infrastructure, Data Engineering, Data Analytics, and Visualization to ML Engineering to and MLOps. Interest and/or experience in some of those fields is an advantage.
Fluent in English and German.
Desired:
Working experience in cloud technologies (AWS, Azure or GCP), Kubernetes and programming languages like Python, Java and Scala.
Practical experience with SQL and NoSQL database technologies and data lakes
Experience with big data technologies (Apache Spark), data streaming (Apache Kafka) and workflow orchestration (Apache Airflow, Dagster)
About the Company
As part of the Reply network with over 8.000 employees and a global footprint, Machine Learning Reply has extensive expertise in the Data Science field across all key industries of our DAX100 clients. The consulting firm offers customized end-to-end data science solutions, covering the entire project lifecycle: whether it is the initial strategy consulting to identify high value cases, project management in classic and agile roles or from data architecture and infrastructure topics to the collection, processing, and quality assurance of data, using state-of-the art Machine Learning algorithms. We empower clients to successfully launch new data driven business initiatives, as well as optimizing already existing processes and products. The company focuses thereby on distributed open source and cloud technologies, to assist companies on their data journey in the most suitable way. To foster long-lasting relationships with our clients and sustainable implementation of our projects, we complementary provide our very own data science and literacy program, the Machine Learning Incubator, to train the next generation of decision makers, data scientists and engineers that our customers need.
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