Stellenbezeichnung: Machine Learning Engineer (m/f/d)
Firma: Machine Learning Reply
Arbeitsort / Location: München, Bayern
Job Beschreibung: Job Description
Machine Learning Reply Germany we work with our clients on leading-edge projects for which we are seeking Machine Learning Engineers to serve our client projects in multiple industries.
Machine Learning Reply, with its sister company in Italy and over 12.000 employees at globally offers consulting and software implementation services with a focus on innovative AI and ML topics like Natural Language Processing, Computer Vision, Time Series Analysis, Machine Learning Platforms, and more.
In our Unit Machine Learning Engineering we currently hire talents with Data Engineering and Cloud know-how who would like to develop not only PoCs but productive machine learning applications or platforms including automatic unit tests and end-to-end tests, automatic deployment pipelines, mechanisms for scaling in the cloud, monitoring solutions and operations support. We call this profile “Machine Learning Engineer”. You should love to see the ML algorithms working for millions of users, devices, sensors, etc., making the world a smarter, safer, more interesting, and/or more efficient place to live.
- Build, maintain, and operate cloud-based solutions with one of the major cloud providers (AWS, Azure, GCP) and big data technologies (Hadoop, Spark, Kafka..)
- Use programming languages such as Python, SQL, Java, Scala to build solutions for solving customers’ problems in Machine Learning domain, as well as, any other domain.
- Utilize CI/CD (GitLab, Jenkins..) and DevOps paradigms to develop, deploy, and scale applications with Infrastructure as code(Terraform, Helm, Ansible), and container-based technologies (Docker, Kubernetes)
- Build and maintain data-intensive applications with big data technologies like Apache Spark, Hadoop, and databases (SQL and NoSQL), using batch or real-time data integration (Kafka, RabbitMQ).
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 between 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 trainings, 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 work equipment
- Public transport ticket within Munich
- Gym-membership subsidy for a gym of your choice
- Flexible work environment between client, Reply office and remote work
- You successfully completed studies in computer science, mathematics, physics, business administration, or equivalent.
- Depending on your seniority, you have 1+ years of work experience in industry or consulting and developing production systems with MLOps/DevOps principles.
- You demonstrate experience with ML and cloud computing platforms (AWS, GCP, Azure), additionally Databricks.
- You have hands-on expertise, and interest in the diverse end-to-end Machine Learning Engineering stack, including Data Engineering, Microservices, Frontend and Backend development.
- You have a high level of customer orientation and excellent communication skills.
- You are willing to travel.
- You are fluent in English and have at least intermediate proficiency (B1) in German (willing to improve).
Nice to Have
- Experience working with modern ML and DL frameworks such as TensorFlow, PyTorch and Keras.
- Knowledge and experience in software engineering best practices.
- Experience with Front-end Web Development Technologies Vue.js, AngularJS, Django, HTML, CSS.
Machine Learning Reply
As part of the Reply network with over 10.000 employees Machine Learning Reply has extensive expertise in the Data Science field across all key industries.
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