Machine Learning Engineer – PySpark, PyTorch, Machine Learning – REF7848E

29 April 2024
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Deadline date:
£159000 - £250000 / year

Job Description

About Zscaler

Zscaler (NASDAQ: ZS) accelerates digital transformation so that customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange is the company’s cloud-native platform that protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. 

With more than 10 years of experience developing, operating, and scaling the cloud, Zscaler serves thousands of enterprise customers around the world, including 450 of the Forbes Global 2000 organizations. In addition to protecting customers from damaging threats, such as ransomware and data exfiltration, it helps them slash costs, reduce complexity, and improve the user experience by eliminating stacks of latency-creating gateway appliances. 

Zscaler was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. Zscaler’s purpose-built security platform puts a company’s defenses and controls where the connections occur—the internet—so that every connection is fast and secure, no matter how or where users connect or where their applications and workloads reside.


At the Premier Cloud Security Provider, we are working with the massive scale of network data, security data, and enterprise data every day. We are seeking out engineers with a passion to build out tools and platforms, process and analyze data at scale, and solve real-world business problems.

As a software engineer for our Machine Learning platform, you have three main responsibilities:

  1. You will architect, build and maintain large-scale distributed systems to support the whole pipeline including data collection, feature engineering, model training, model evaluation, model deployment, and real-time serving.
  2. You will apply analytical and math/statistics skills to stay on top of data and to ensure results are coherent and reliable.
  3. You will solve complex real-world business problems (e.g., threat detection, automation, and business intelligence) by working closely with various stakeholders including data scientists, product management, and product engineering teams.

You may not have any prior data science and ML background but you need to have a desire in building up knowledge in this area. For example, we expect you to have tremendous curiosity in how the data can and will be utilized by the data scientist in order to have a very effective collaboration with data scientists.

Required Skills:

3+ years of prior work experience as a Software Engineer or ML platform engineer

Very strong algorithm and programming skills in building out data collection/processing infrastructure, Machine Learning model training, and serving platforms

Very strong Python and SQL scripting skills

2+ year of experience using distributed data processing such as Spark, BigQuery or Apache Beam

2+ year of experience with event messaging such as Kafka, RabbitMQ, etc

2+ years of experience working with Docker, Kubernetes

– Ability to learn, evaluate and adopt new technologies

– BS Degree in Computer Science or related field


Desirable Skills:

Experience with Go, C++, or Javascript

Experience with setting up SQL/NoSql database such as Postgres, MongoDB, Redis, and table schema

1+ year of experience with ML automation platforms such as Kubeflow, Airflow or MLFlow

– Experience with data serialization techniques and data stores for persisting events

– Experience with Google cloud (or other public cloud)

– Experience with building quality software by writing robust interfaces, considering design principles, and applying sound testing practices

– Ability to lead and execute projects from start to finish

Knowledge of NLP/Text mining techniques and related open-source tools

– Familiarity with networking and networking security

– Excellent interpersonal, technical, and communication skills

– Advanced degree in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Math or other quantitative fields from a reputed university (Ph.D. a plus)



#LI – YK1

By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.

Zscaler is proud to be an equal opportunity and affirmative action employer. We celebrate diversity and are committed to creating an inclusive environment for all of our employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status or any other characteristics protected by federal, state, or local laws.

See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.

Pay Transparency

Zscaler complies with all applicable federal, state, and local pay transparency rules. For additional information about the federal requirements, click here.

Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.