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Machine Learning Engineer at CybelAngel. 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 !. Company Location: France.