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Machine Learning Engineer

Employer
SKILLFINDER INTERNATIONAL
Location
London
Salary
700.00 GBP Daily
Closing date
16 Aug 2022

View more

Employer Sector
Technology, ICT & Telecoms
Contract Type
Contract
Hours
Full Time
Travel
None
Job Type
Data Engineering

Machine Learning Engineer

Duration: 6-months (Strong likelihood of a renewal)
Location: Remote for (UK Based)
(inside IR35)

Role/Individual:

  • Deploying the latest NLP techniques such as Transformer Models in production, with awareness of the challenges.
  • Creating performance metrics and tracking processes to measure the effectiveness of Data Science solutions
  • Conceptualizing necessary data governance models to support the technical solution and assure the veracity of the data
  • Working collaboratively with other members of the Data Science, Data Engineering, and Information Architecture teams to innovate and create compelling data-centric stories and experiences
  • Proficient with programming languages in Big Data platforms, like Python, R, Scala
  • Knowledge of at least one of the mainstream deep learning frameworks such as PyTorch, TensorFlow
  • Understanding software development best practices
  • GCP platform: Dataflow, Composer, BigQuery, Vertex AI, or similar techniques in other cloud platforms
  • MLOps - MLFlow, Kubeflow, BentoML, or similar
  • Productionising machine learning pipelines with Apache Beam and Apache Airflow
  • Demonstrated Data Science consultancy skills, eg running hypotheses workshops, mentoring more junior team members, preparing reports, and presenting data science results.
  • Skilled to communicate with a variety of stakeholders in the organization
  • Planning and organization skills so as to work with a high-performance team, handle demanding clients, and multitask effectively and in an agile way
  • 5+ years of experience in AI, data science, data engineering, and/or other technology-related capabilities in one or multiple industries. Experience in the Financial Service sector, in particular ESG analytics and risk management, is preferred.
  • BSc (ideally MSc or Ph.D.) in Computer Science, Statistics, Engineering, or similar technical field

A combination of one or more of the following:

  • Proficient with programming languages like Python, R, Scala,
  • Proficient with Git, Linux, Docker
  • Software Engineering best practices and Object-Oriented Programming
  • Skills in big data technologies like Hadoop, HDFS, Spark, Apache Beam, Apache Airflow
  • SQL and NoSQL databases

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