Machine Learning Engineer, CybelAngel

€42-47k

+ 5 % Bonus, based on company and individual performances

Python

NumPy

Pandas

Scikit-Learn

Entry and Junior level

Paris

Data risk management & protection platform

Be an early applicant

Data risk management & protection platform

101-200 employees

B2BSecuritySaaSCyber Security

Be an early applicant

€42-47k

+ 5 % Bonus, based on company and individual performances

Python

NumPy

Pandas

Scikit-Learn

Entry and Junior level

Paris

101-200 employees

B2BSecuritySaaSCyber Security

Company mission

To give our customers complete confidence in their external security posture through Innovative Technology, Profound Accuracy, Focus Priority and the Speed to Act before an incident can occur.

Job

Company

Role

Who you are

A first experience as an ML Engineer or in a similar role
Good data modelling skills
Ability to write robust code in Python
Familiarity with standard libraries (Scikit-learn, XGBoost, pandas, numpy, ...)
Communication skills
Ability to work in a team
Good analytical and problem solving skills
You already worked with a cloud provider (not necessarily GCP!)
Organised

What the job involves

Introducing intelligence at the various levels of our processing pipeline is therefore a crucial issue for CybelAngel: we want to filter out non-sensitive elements
Our Data Science team has the mission to make our filtering algorithms as intelligent as possible, in order to optimize and facilitate the processing of security incidents delivered to our customers
Our Machine Learning Engineers build systems to measure models drift, build robust pipelines to ease production release and models retrain, and help the data scientists on the good practices of software development
Automatic retrain when we measure a drift in the performances will be the key project in the next few years!
They are also in charge of designing Machine Learning models from data analysis to production release with the data scientists
Study and implement Data Science's POCs
Design Machine Learning algorithms
Research and implement ML algorithms that seem to be relevant
Conduct Machine Learning tests and experiments
Train Machine Learning models required
Improve existing packages
Stay up-to-date with the latest advances in the field
Classic ML and GenAI
Our (current) stack
Language: Python, SQL
Databases: ElasticSearch, BigQuery
Librairies: Pandas/Polars, Scikit-learn, XGBoost, Matplotlib, Streamlit, Plotly, HuggingFace
MLOps: Gitlab CI, Docker, Kubernetes, Terraform, ZenML, MLFlow, Kubeflow
Environment: Jupyter notebook [gcp]
Other: GCP, Datadog, Dataflow, Linear

Application process

30’ call with Pierre, recruiter to make sure expectations from both ends have a good chance to match
30’ call with Fabien, Data Science Manager to evaluate skills and culture fit
60' meeting with the whole Data Science team to present the technical test that you prepared at home => have the chance to present your methodology and added value

Our take

Cybercrime is an ever-present threat for all organisations, both large and small. And certain sectors, such as healthcare, are especially vulnerable to data leaks. CybelAngel is a digital risk protection platform that uses its robust tech to scour each layer of the web for data leaks.

Its approach involves maximising encryption defences, monitoring all remote connections, and ensuring employees are aware of the risks. With an aim to provide a rapid scanning speed of under 24 hours, customers are able to monitor their own data and detect when it is exposed. This allows businesses to have ownership of their own data security.

Its definitely an attractive proposition, as the issue of data privacy continues to be a hot topic. In the evolving cyberthreat landscape, CyberAngel continues to meet new business requirements and improve efficiency as it expands its global ecosystem and develops new security solutions.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

-21% employee growth in 12 months

Glassdoor (3.8)

Company

Funding (last 2 of 4 rounds)

Feb 2020

$38.7m

SERIES B

Oct 2018

$11.8m

SERIES A

Total funding: $55.2m

Company benefits

PTO (22 days per year) & Holidays (11 per year)
Monthly phone/Internet Stipend
Opportunities for travel domestically and internationally
Friendly and collaborative work environment
Regular team building events

Company HQ

L'Europe, Paris, France

Leadership

Erwän Keräudy

(Co-Founder & CEO)

Former Finance Lecturer at ESCP Business School, Credit Trader at Societe Generale and Deputy Chief Investment Officer at SBI Mutual Fund.

Stevån Keråudy

(Co-Founder & CTO)

Co-founded and was the CTO of Mozaick, and previously worked as a Consultant at Accenture.

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