Machine Learning Engineer

at  Callsign

Russian hacker, Vladimir Leonidovitch Levin, attempted the biggest bank heist the world had ever seen via dial-up internet in 1994, Zia Hayat, Callsign CEO and founder, was hooked - armchair fraud became a real possibility. From this moment, Zia knew he wanted to play a part in stopping the bad guys and securing the internet for all. Founded In 2012, Callsign’s mission has been to make Digital Identity simple and secure for everyone and everything. In that time, we’ve grown to over 200 employees, opened offices in Singapore and Abu Dhabi, been recognised as a WEF Global Innovator and our technology is being used by many of the world’s leading financial institutions to keep millions of consumers safe.
But we aren’t stopping here. The identity revolution has only just begun, and we are looking to hire the brightest and inquisitive

WHAT THE JOB INVOLVES:

• Looking for excellent engineers to join their machine learning engineering team, responsible for productionising state-of-the-art ML models for real-time behavioral prediction and anomaly/threat detection
• Work across the machine learning life-cycle productionising state-of-the-art behavioral 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
• (Desirable) Desirable backgrounds and tools in our tech-stack - none of these are requirements, but are a bonus if you have them

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 python’s 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

Please refer the Job description for details