Senior Software Engineer – Machine Learning (SAGEMAKER – Data Ingest) [UK]

at  Spyrosoft

REQUIREMENTS

• SageMaker
• Data Ingest/processing: Kafka, Spark, Kinesis, Flink (desired), Feature Stores (Desired)
• AWS, Lambda, EventBridge, CodeBuild/CodePipeline
• OpenSearch (Desired)
• Python
• JavaScript/TypeScript
• MLOps (Desired)

EXPERIENCE

• A degree in Computer Science, Software Engineering, or a related field or similar work based experience.
• Proven experience as a Senior Software Engineer ideally with a focus on media-related projects.
• Very good working knowledge of standard software development frameworks, techniques and methodologies.
• Experience with providing coaching and mentoring
• Ability to work collaboratively in a team, contributing to the development of business scenarios.
• Knowledge of software development tools and technologies.
• You are flexible and curious in your approach
• Strong analytical and problem-solving skills

ROLE OVERVIEW

As a Senior Software Engineer, you will be working with our media client who produces an incredibly varied range of content: from video, audio, and text; from comedy, drama, news, and educational content; and content produced all around the UK. With so much content being produced, it can be difficult to get the right content to the right person. We are aiming to become more personalised, to get our audience the content they love, quicker.
The recommendations squads have been building out a common recommendations platform in AWS, utilising SageMaker to enable Data Scientists to experiment with recommendations.
We are looking at expanding and investing in the audience facing recommendations platform. We’ve recently been going through a re-platform effort on AWS utilising SageMaker and MLOps practices. We want to enable our Data Scientists to do their best work, to experiment, and improve our recommendations offering. In order to enable our Data Scientists to experiment, we need to build out our Data Ingest pipelines to feed into our MLOps platform.

ESSENTIAL KEY SKILLS AND RESPONSIBILITIES

You will have:

• experience building Data Ingest pipelines and working with Feature Stores
• experience working with feature stores to utilise that data
• experience working with MLOps (CI/CD, TDD, automation of testing, operational excellence)
• experience of modern Python development software engineering best practices
• experience of AWS services such as SageMaker, S3, VPC, KMS
• experience in feature engineering, data pre-processing, data pipelines, feature store
• knowledge of CI/CD pipelines such as CodeBuild or CodePipeline
• a strong willingness to learn and be a keen team player
• professional experience of working in projects using Agile development processes
• experience of writing and taking responsibility for technical documentation