Who you are
- Strong demonstrated experience using ML Training frameworks (mainly TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)
- Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance
- Proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)
- Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)
- Experience with high-volume data processing and real-time streaming architectures
- Strong understanding of recommendation system design and personalisation algorithms
- Familiarity with Generative AI and its applications in production settings
- Good communication and analytical problem-solving skills
- If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Desirable
- Experience working on OTT platforms
- Experience in Scala
What the job involves
- Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis
- Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets
- Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance
- Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement
- Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs
- Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems
Contract Details
- 12 Month Fixed Term Contract
- Location: London, 2 days a week in office (West London, UK)
- End Date: September 30, 2026
- Level: Senior and Expert level
- Technologies: Python, Scala, TensorFlow, Kubeflow, PyTorch
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Interim Senior ML Engineer in London employer: Go Fractional
At Cambridge Spark, we pride ourselves on being an exceptional employer that values autonomy and expertise. As a Fractional CISO, you will enjoy the flexibility of remote work while contributing to a dynamic security strategy for our clients. Our culture fosters professional growth through independent advisory roles, ensuring you have the opportunity to make a significant impact in a supportive environment focused on delivering high-quality outcomes.
