Machine Learning Engineering

7 days left

Skillfinder International
London, United Kingdom
£630 - £700
15 Nov 2022
15 Dec 2022
Job Function
Industry Sector
Finance - General
Employment Type
Full Time
Duration: 6-months (Strong likelihood of a renewal)

Location: Remote for (UK Based)

(inside IR35)


• Designing and building big data pipelines with machine learning workloads that are repeatable/scalable for extremely large datasets.

• Deploying the latest NLP techniques such as Transformer Models in production.

• Creation of performance metrics and tracking processes to measure the effectiveness of Data Science solutions

• Data governance models to support the technical solution and assurance of the veracity of the data

• Proficiency with programming languages in Big Data platforms, like Python, R, Scala

• Strong 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

• Track record in staying conversant in new analytic technologies, architectures, and languages - where necessary - for storing, processing, and manipulating this type of data

• 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

• Team management experience preferred


• 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 PhD) in Computer Science, Statistics, Engineering, or similar technical field

• 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