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Job Description:
What you'll do:
Design & implement machine learning model pipelines to improve efficiency, speed and effectiveness of our ML operations.
Be collectively responsible for designing, developing & maintaining technical infrastructure to train and serve models at scale on cloud platforms (e.g. GCP, AWS).
Be familiar CICD systems to ensure quick release of new models.
Become a valued member of an autonomous, multi-functional team and contribute to growing the skills and knowledge of your peers.
Facilitate the collaboration with other specialists, researchers, data scientists and product owners in order to ensure we deliver the maximum value to our customers.
Requirements:
Experience with containerisation technologies (Docker, Kubernetes).
Comfortable with data pipeline technologies/ ML-ops frameworks such as Spark, Beam, Kubeflow & Airflow.
Knowledge of ML frameworks such as PyTorch, Keras, Sklearn & Huggingface.
Familiar with Gitops workflows (Jenkins, Argo, Spinnaker).
You are proficient in a programming language such as Python or Java/ Scala.
You can easily work with a range of data stores within the relational SQL world (PostgreSQL, bigquery,), NoSQL databases & key-store databases (Cassandra, Hbase based dbs).
You have a strong computer science and programming fundamentals.
Comfortable with machine learning concepts & statistics.
You have a deep understanding of system design and data structures.
You care about quality, details and you know what it means to ship high-quality code that is easy to maintain and extend, test coverage is your pride.
Benefits
30 days’ annual leave per year (inc public holidays)
Generous stock options scheme with the wider Arabesque Group.
10% of your working time is dedicated for you to explore other projects & - technologies.
