Machine Learning Engineer
CybelAngel
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Résumé du poste
Qualifications
- Expérience préalable comme ML Engineer.
- Capacité à écrire un code robuste en Python.
- Familiarité avec les bibliothèques standards.
Responsabilités
- Étudier et mettre en œuvre des POCs en data science.
- Concevoir et tester des algorithmes de machine learning.
- Former les modèles requis pour le machine learning.
Connaissances
Formation
Outils
Description du poste
This range is provided by CybelAngel. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Our job everyday is to protect the data and critical assets of businesses world-wide by discovering hidden vulnerabilities... before the bad guys do!
At CybelAngel, we see beyond perimeters to protect businesses from the most critical cybersecurity threats. Fortune 500 Global to mid-size companies world-wide, trust CybelAngel's global of approximately 150 team members, to protect their businesses from digital threats. With a combination of advanced machine learning, cyber analysis expertise, and a powerful suite of software solutions, CybelAngel detects and resolves our clients potential threats, long before they can fall into the hands of cyber criminals.
Our capabilities expand every day to uncover new risks, detect more threats, protect more clients, and create new possibilities for our employees.
With offices in Boston, Paris, and London, CybelAngel's global footprint allows for a thriving hybrid, office and remote-work environment. We are looking for exceptional ‘go-getters' who share our ambitious vision, innovative culture, high commitment to ethics, and enthusiasm for being the best possible place to work!
Our values
- Be Bold
- Be Curious
- Stronger Together
The Data Science Team
We process billions of documents every day to alert our customers in case of data leaks! Our goal is to spot sensitive data in a massive amount of documents.
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.
Your responsibilities
- 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
- Stay up-to-date with the latest advances in the field
- Classic ML and GenAI
Our (current) stack
- Language: Python, SQL
- Librairies: Pandas/Polars, Scikit-learn, XGBoost, Matplotlib, Streamlit, Plotly, HuggingFace
Our job everyday is to protect the data and critical assets of businesses world-wide by discovering hidden vulnerabilities... before the bad guys do!
At CybelAngel, we see beyond perimeters to protect businesses from the most critical cybersecurity threats. Fortune 500 Global to mid-size companies world-wide, trust CybelAngel's global of approximately 150 team members, to protect their businesses from digital threats. With a combination of advanced machine learning, cyber analysis expertise, and a powerful suite of software solutions, CybelAngel detects and resolves our clients potential threats, long before they can fall into the hands of cyber criminals.
Our capabilities expand every day to uncover new risks, detect more threats, protect more clients, and create new possibilities for our employees.
With offices in Boston, Paris, and London, CybelAngel's global footprint allows for a thriving hybrid, office and remote-work environment. We are looking for exceptional ‘go-getters' who share our ambitious vision, innovative culture, high commitment to ethics, and enthusiasm for being the best possible place to work!
Our values
- Be Bold
- Be Curious
- Stronger Together
The Data Science Team
We process billions of documents every day to alert our customers in case of data leaks! Our goal is to spot sensitive data in a massive amount of documents.
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.
Your responsibilities
- 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
Your preferred experience
- 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
If you do not meet the requirements but you think you are a great fit, you are welcome to apply and explain why !
Our Product & Engineering Culture
️ Small teams & short iterations
Culture of sharing, pair and mob programming, when it makes sense
Quality time dedicated to technical design
️Half the software engineers have over 10 years of experience
Voyager Program to change team temporarily and discover how they work #becurious
️ Cooldown week dedicated to learning and experimenting
Our Benefits
Salary range: 42-47k based on your level of seniority and competencies you will demonstrate during the hiring process
5 % bonus, based on company and individual performances
Debit card for paying for lunch, with company contribution
️Healthcare insurance, with company contribution
️Remote allowance
Referral bonus for every new CybelAngel we recruit based on your recommendation
️ Monthly credits to spend with CSE partner
️5 weeks of holidays and RTT
Subsidy for one sporting event per year
️ Legal Care Service solution
Flexible work environment : flexible hours, remote (+45% of our team works fully remotely), right to disconnect charter, sick child leave paid
Diversity & Inclusion
Advocate team
Very friendly and benevolent atmosphere
Multicultural team (19 nationalities)
️34% women
Index Egapro 84/100
We are committed to creating an inclusive workplace and giving everyone an equal opportunity to succeed, regardless of their background, identity, or life experiences. We value diversity and believe that every individual, no matter their journey, deserves a chance to contribute and thrive.
Your hiring journey with us
- 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
- Seniority levelEntry level
- Employment typeFull-time
- IndustriesTechnology, Information and Internet
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