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
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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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