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Callsign
,
London, Greater London
ML Engineer
Overview
Job Description
Callsign is rapidly expanding its technology platform and is looking for excellent engineers to join their machine learning engineering team, responsible for productionising state-of-the-art ML models for real-time behavioural prediction and anomaly/threat detection. Responsibilities * Work across the machine learning life-cycle productionising state-of-the-art behavioural prediction and anomaly/threat detection models. * Developing CI/CD testing pipelines. * Collaborating closely with the Data Science research team to automate research tasks and applying software and testing best practices to machine learning source code. * Collaborating closely with the Data Engineering and Dev-Ops teams on the deployment and monitoring of live production models. * Work across the machine learning life-cycle productionising state-of-the-art behavioural prediction and anomaly/threat detection models. * Developing CI/CD testing pipelines. * Collaborating closely with the Data Science research team to automate research tasks and applying software and testing best practices to machine learning source code. * Collaborating closely with the Data Engineering and Dev-Ops teams on the deployment and monitoring of live production models. Requirements * Strong software engineering skills, including unit and integration testing. * Experience in academia or industry on projects leveraging Machine Learning. * Ability to optimise model code that heavily uses pythons mathematical libraries (numpy, pandas etc) for both batch and online operation. * Experience with python environment managers conda, venv or similar. * Experience developing applications for containerised environments (Kubernetes, Docker, Istio/Linkerd, etc.) * Familiarity with CI / CD pipelines. * Proficiency with relational databases. * Msc/PhD in Computer Science, Machine Learning or a similar quantitative field. * An interest in bayesian machine learning, anomaly/novelty detection, one-shot learning and supervised learning. * An interest in fraud prevention and cybersecurity. * Familiarity with NoSQL databases. * Experience working in agile teams. * Experience working with QA engineers to triage production bugs. * Experience with Java/Scala. * Experience with cloud compute platforms (AWS, GCP, Azure, etc.) * Experience with big data technologies (Spark, Hadoop or Hive etc.) * Experience with Kubernetes and Docker. * Experience with workflow managers such as Airfow, MLFlow or Kubeflow. * Experience with the ELK stack. Bonus points: Desirable backgrounds and tools in our tech-stack - none of these are requirements, but are a bonus if you have them: Benefits Automatic Option: * Health Insurance single * Life Insurance * Employee Assistance Program * 3 months full pay maternity & 2 weeks full pay paternity (if the statutory minimum is met) * 25 days of annual leave + Callsign Bank Holiday (not included in holiday allowance) * Free Financial Advise Optional: * Cycle to work scheme * Wills and Estates our benefits provider has partnered with a third party who offers a discount * Home Utilities our benefits provider has partnered with a third party who offers a discount * Cycle Insurance * Health cash plans * Cyclist protection * Discounted gym membership