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Machine Learning Engineer

CallsignOnsite
This job is no longer open

Description


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

Benefits


  • Health Insurance
  • Visa costs including 1 month paid hotel stay
  • Annual Airfare Allowance for the home country
  • 3 months full pay maternity leaves & 2 weeks full pay paternity leaves
  • 25 days of annual leave + Callsign Bank Holiday (not included in holiday allowance)
  • Competitive Salary
  • Gratuity as EOSB

  • If you feel you have the above skills we would love to hear from you!

This job is no longer open

Life at Callsign

Friction-free Identification and Authentication By using all of the thousands of data points available such as typing or swiping techniques, location, online habits, face recognition, devices, and yes even passwords, we can determine someone is who they say they are; we even know the Monday person can behave differently to the Friday person. Most of these data points are friction-free for the user, and so we use these to determine that someone's behaviour is within their normal pattern. Where there is a veering from the norm we then intelligently introduce further tests, avoiding a rules-based approach that can be replicated by the bad guys. We have the lowest false positive rates in the industry and zero breaches thanks to our inbuilt malware detector. As a result, users can get on with their digital lives whilst businesses improve customer engagement, increase productivity and reduce the risk of fraud. Callsign enables customers and employees to #GetOn with their digital lives with friction-free identification and authentication.
Thrive Here & What We Value- Collaborative and fun team- High standards for self and peers- Importance of balancing fun with hard work- Teamwork and mutual respect- Continuous improvement mindset- Positive attitude towards challenges- Open communication channels- Encouragement of creativity and innovation- Supportive environment for growth- Commitment to excellence

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