Vacancies at Relx

Responsibilities

As a senior machine learning operations engineer on our team, you will work on new product development in a small team environment writing production code in both run-time and build-time environments. You will help propose and build data-driven solutions for high-value customer problems by discovering, extracting, and modeling knowledge from large-scale natural language datasets. You will prototype new ideas, collaborating with other data scientists as well as product designers, data engineers, front-end developers, and a team of expert legal data annotators. You will get the experience of working in a start-up culture with the large datasets and many other resources of an established company. You will also:

• Develop and implement a strategy for continuous improvement of our Machine Learning Ops including versioning, testing, automation, reproducibility, deployment, monitoring, and data privacy
• Develop and report on ML Ops metrics such as deployment frequency, lead time for changes, mean time to restore, and change failure rate
• Collaborate with data scientists, data engineers, API engineers, and the dev ops team
• Build scalable data ingestion and machine learning inference pipelines
• Scale up production systems to handle increased demand from new products, features, and users
• Provide visibility into the health of our data platform (comprehensive view of data flow, resources usage, data lineage, etc) and optimize cloud costs
• Automate and handle the life-cycle of the systems and platforms that process our data

Requirements

• Masters degree in Software Engineering, Data Engineering, Computer Science or related field
• 5 years of relevant work experience
• Strong Scala and Python background
• Experience with Apache Spark and/or Ray
• Knowledge of AWS, GCP, Azure, or other cloud platform
• Knowledge of current principles and frameworks for ML Ops
• Experience with ML Ops technologies such as ML Flow, DVC, Grafana, DataHub, Databricks
• Experience with machine learning technologies such as PyTorch, TensorFlow, AWS Sagemaker
• Experience with CI/CD pipelines, including Jenkins or Git Actions
• Experience with Docker containerization or Kubernetes orchestration
• Experience in improving data security and privacy, and managing and reducing cloud costs
• Knowledge of API development and machine learning deployment

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Responsibilities

As a senior data engineer on our team, you will work on new product development in a small team environment writing production code in both run-time and build-time environments. You will help propose and build data-driven solutions for high-value customer problems by discovering, extracting, and modeling knowledge from large-scale natural language datasets. You will prototype new ideas, collaborating with other data scientists as well as product designers, data engineers, front-end developers, and a team of expert legal data annotators. You will get the experience of working in a start-up culture with the large datasets and many other resources of an established company. You will also:

• Build and scale data infrastructure that powers real-time data processing of billions of records in a streaming architecture
• Build scalable data ingestion and machine learning inference pipelines
• Build general-purpose APIs to deliver data science outputs to multiple business units
• Scale up production systems to handle increased demand from new products, features, and users
• Provide visibility into the health of our data platform (comprehensive view of data flow, resources usage, data lineage, etc) and optimize cloud costs
• Automate and handle the life-cycle of the systems and platforms that process our data

Requirements

• Masters in Software Engineering, Data Engineering, Computer Science or related field
• 2-3 years of relevant work experience
• Strong Scala or Java background
• Knowledge of AWS, GCP, Azure, or other cloud platform
• Understanding of data modeling principles.
• Ability to work with complex data models.
• Experience with relational and NoSQL databases (e.g. Postgres, ElasticSearch/OpenSearch, graph databases such as Neptune or neo4j)
• Experience with technologies that power analytics (Spark, Hadoop, Kafka, Docker, Kubernetes) or other distributed computing systems
• Knowledge of API development and machine learning deployment

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About the Role

As a Technical Editor, you will be part of the LN Global Legislation team and support the UK team to deliver Halsbury’s Statutes, Halsbury’s Statutory Instruments and Butterworths Handbooks publications in all media, using the most operationally efficient processes.

Responsibilities

• Updating publications with new legislation and their amendments, following house style.
• Ensuring all material included is accurate by conducting detailed legal research and closely monitoring legal developments.
• Planning, organizing and editing material for publication as discrete volumes/titles, liaising with senior team members and others with regards to content
• Collaborating closely with production team and deal with day-to-day operational problems that occur within own area.
• Respond effectively, and in a timely, professional manner, to queries from external and internal customers.
• Contributing to commercial development/enhancement of the product as appropriate, generating ideas to improve functionality (online or offline) of content.
• Helping to identify and drive cost savings and revenue enhancing/protecting opportunities across team and department.

Requirements

• Experience in legal publishing and/or legal practice experience.
• Experience demonstrating a clear understanding of the way English and Welsh law develops and of conducting independent legal research.
• Possess editorial skills and excellent written English. Ability to understand, navigate and present complex legal material articulately and accurately.
• Show interpersonal skills, a positive attitude, and professional manner for routine contact with geographically diverse authors/consultants, colleagues, customers and vendors.
• Have time management skills to meet rigid and frequent deadlines.
• Proficient in MS Office (Outlook, Word, Excel), familiarity with content management systems, and an interest in learning new systems/technologies.