Python Job: Machine Learning Engineer

Job description

At Machine Learning Reply Austria we strive to work on leading-edge data science projects with our clients for which we are seeking Cloud Engineer consultants with a strong technical background.

Machine Learning Reply, with its sister companies in Italy and Germany and over 8500 employees at Reply globally, is a fast-growing consultancy focused on solving problems with Data Science, Cloud technologies and the right organizational frameworks as their backbone. We are a tight knit, laid back, but seriously motivated unit that aims to be involved at conferences and in community of practice with our tech partners.

We offer tailor-made end-to-end cloud-based solutions in the Data Science area that cover the entire project life cycle - from initial strategy consulting to data architecture and infrastructure issues to data processing and deployment of production-ready algorithms.

We have a vast expertise in every step of the Data Science implementation spectrum in all key industries of the German HDAX-companies. With focus on open source and cloud technologies we enable our customers to successfully introduce and implement new data-driven solutions and to optimize already existing processes and products while simultaneously adapting to cloud technologies.

Tasks

Use your cloud know-how and work closely with our customers to find out what the perfect (cloud) technology is for them!

• Through your knowledge you are able to design innovative, technical approaches for cloud solution architectures
• Your designed cloud architectures (based on AWS, Microsoft Azure or Google Cloud) will be implemented by you also always considering DevOps / MLOps
• You will not be alone and will work closely with colleagues from Data Science or Data Engineering to jointly develop data-intensive applications

such as data warehouses, data lakes and/or data platforms

• You enjoy brainstorming, conceptualization and final implementation. You therefore like to accompany the complete LifeCycle by creating specifications, code and presentations for your solutions.
• As part of the Reply network, you join communities of practice, participate in hackathons and use all available learning resources

What we offer you:

• We offer you for this position according to the collective agreement for employees in data processing and information technology a gross monthly salary of at least EUR 3215 (Consultant) or EUR 4286 (Senior Consultant) depending on your previous experience.
• Access to work on projects across industries (large and mid-market companies in Banking, Insurance, Automotive, Retail, etc.)
• Very active group social program - including conference funding, team building, group events, Reply Exchange
• Recognition for Innovation to foster your personal development
• Work in an open, flat environment, within a broad Reply knowledge sharing network (more than 90 autonomous Reply groups across 8 countries)
• Office space in downtown Vienna with access to Stammstrecke
• Training and certification encouraged
• Home-office contracts
• State of the art work equipment
• Award winning office spaces for an excellent work experience
• Public transport ticket within Vienna
• Gym-membership subsidy for a gym of your choice
• Flexible work environment between client, Reply office and remote work

Requirements

• A university degree in (business) informatics, mathematics, statistics (or comparable) and at least 3 years of professional experience in industry or consulting
• Experience in the development of data-intensive applications such as data warehouses, data lakes and / or data platforms
• You have knowledge in code development using Java/Scala or Python
• You are familiar with relational databases as well as ideally NoSQL databases (e.g. Oracle, Aurora, Mongodb, Cassandra)
• Deep understanding in the development of Machine Learning applications as well as solutions based on Big Data technologies such as Hadoop or Spark or their cloud-based equivalents
• Very good English and good German skills as well as willingness to travel nationally