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Title: Machine Learning Engineer
Type: Contract (4-months minimum, extensions likely)
Location: Remote
About Ovyo
Ovyo is a B2B services company providing flexible engineering teams and talent solutions to the streaming, media, satellite, and communications industries. With a global footprint across the UK, India, Portugal, South Africa, Brazil, the US, and Eastern Europe, we work on a mix of long-term client engagements and fast-paced consulting projects. Our engineers build the platforms that shape how the world consumes video and connects — while accelerating their own careers along the way.
The Role
We’re looking for a Machine Learning Engineer to design, build, and operate large-scale machine learning systems, with a strong focus on recommendation engines and personalised content discovery.
You’ll work closely with client engineering and product teams to deliver production-ready ML solutions that are scalable, reliable, and high-performance in real-world environments.
Responsibilities
- Design, build, deploy, and optimise end-to-end machine learning solutions in production
- Develop and enhance recommendation systems supporting personalised user experiences
- Integrate ML models with data pipelines and backend platforms
- Collaborate with engineers, product managers, and stakeholders to deliver ML-driven features
- Ensure ML systems are scalable, observable, and reliable
- Communicate technical concepts and insights clearly to both technical and non-technical audiences
Requirements
- Proven experience as a Machine Learning Engineer working with large-scale data systems
- Strong hands-on experience with Java, Python, and SQL
- Experience building and deploying production-grade machine learning models
- Hands-on experience with TensorFlow 2.x
- Solid understanding of recommendation systems, including Matrix Factorization and Factorization Machines
- Experience with Apache Spark and Apache Flink
- Experience working in Kubernetes (K8s) environments
- Familiarity with OpenSearch or similar search technologies
- Hours flexibility - some cross over with the US teams
Key Skills
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