Software Engineer
3 tygodni temu
technologies-expected :
Python
Splunk
Git
technologies-optional :
Microsoft Azure
Apache Spark
Splunk
Grafana
about-project :
We are looking for a Machine Learning Engineer, to join our growing Data Science Engineering team. You’ll work with other engineers, data scientists, product managers, systems engineers, and analytics professionals to help deliver valuable and innovative outcomes for our customers. You’ll work within and across our Engineering and Data Science teams, delivering scalable products that improve how we serve our customers and run our operations.
This role would suit someone with previous experience working as a ML Engineer or a Software Engineer.
responsibilities :
Participating in group discussions on system design and architecture
Working with product teams to communicate and translate needs into technical requirements
Working alongside our Data Scientists, Software Engineers and Product teams across the software lifecycle
Delivering high quality code and solutions, bringing solutions into production
Performing code reviews to optimize technical performance of data science solutions.
Supporting production systems, resolving incidents, and performing root cause analysis
Look for how we can evolve and improve our technology, processes and practices
Sharing knowledge with the immediate engineering team
Applying SDLC practices to create and release robust software
requirements-expected :
You come from either a Software Engineering or ML Engineering background with a good understanding Programming (Python), Machine Learning and MLOps and bringing data science solutions into production.
2-3 years of experience working as a Software Engineer (experience working with Python Machine Learning project is beneficial)
Strong Software Engineering skills, with experience of different programming languages and a good grasp of at least one language, ideally Python
A background or understanding of the retail sector, logistics and/or ecommerce would be advantageous but is not required.
Awareness of emerging MLOps practices and tooling would be an advantage e.g. feature stores and model lifecycle management.
Customer focus with the right balance between outcome delivery and technical excellence.
The ability to apply technical skills and know-how to solving real world business problems.
Knowledge of building scalable and resilient systems. Practical experience is advantageous but not required.
An analytical mind set and the ability to tackle specific business problems.
Use of version control (Git) and related software lifecycle tooling (CI/CD).
Desirable experience with tooling for monitoring, logging and alerting e.g. Splunk or Grafana.
Understanding of common data structures and algorithms.
Experience working with open-source Data-Science environments.
Knowledge of open-source big-data technologies such as Apache Spark is desirable, but not required.
Experience building solutions that run in the cloud, ideally Azure is desirable, but not required
Experience using job scheduling tools, like Airflow, is desirable but not required
Experience with software development methodologies including Scrum & Kanban
offered :
Permanent contract from the go – as a sign of our trust in your abilities
MacBook as your tool for work
Learning opportunities - certified technical training and learning platforms like Udemy, Pluralsight and O’reily
Referral Bonus
Sports activities with a personal trainer in the office
Additional 4 days of paid leave to support your well-being and family life
Up to 20% yearly salary bonus – based on both individual and business performance
Private healthcare (LuxMed)
Cafeteria & Multisport
Supporting those, who are not yet eligible for full holiday entitlement, by expanding their pool from 20 to 25 days
Relocation Help
Heightened income costs (KUP)
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