Cyril LAY
Senior Data & ML engineer
How can I help?
I am a Machine Learning Engineer that specialises in generative AI & LLMs.
Having spent a number of years working as a full time data engineer and ML engineer, I am now self-employed and work on a contract basis.
I have a masters degree in computer science with a specialisation in data mining.
My contracts usually involve architecture, development, teaching or auditing.
I enjoy working independently and as part of a team.
5
years of experience
15+
clients
100%
satisfaction rate
Please get in contact on linkedin if you'd like to explore opportunities to work together.
What can I do for you?
Data management
Manage and clean your company's data, integrate external sources and expose it to other applications, such as business intelligence, with ETL pipelines.
Micro services
Architecture and deploy resilient micro services for your organization through Docker/Cloud/APIs.
CI/CD
Automate, speed-up and optimize the integration, delivery and deployment of your applications.
Skillset
I am a back-end systems specialist and data expert; however, I also have experience as a full stack engineer and can pick up new technologies quickly.
My mission is to make sure your organization's data is well prepared, clean and reliable. I can help you create large scale data pipelines that may involve bringing many different systems together.
As a data engineer, I can help you choose the right tools for the job, and combine them to create solutions to enable your company’s business processes with data pipelines.
Check
out how I helped MyTraffic in collecting
and
leveraging pedestrian
footfall data to predict best retail locations...
Check
out the big data pipelines I developed for the BI team at
Gumgum....
Languages
Frameworks
My mission is to help you understand if and where machine learning can be useful for your company, and implement the AI models and systems for you.
As a data scientist, I can help you create data pipelines for machine learning (extraction, cleaning, augmentation) and deploy state of the art models suited to your problematic.
Check out my work on
fake faces recognition on a
500GB
video dataset…
Check out my work on
building a bot detection
engine…
Check out my
open-source image classification
app…
Languages
Frameworks
I can work with your team to shorten and optimize your application lifecycle process, and facilitate fast and clean deployments via standardization and automation. I am also able to architect your systems using a cloud provider of your choice (AWS, GCP, Azure, IBMCloud)
If you need to deploy CI/CD pipelines across your organization or expose applications as micro-services, on-premises or on the cloud, I can do it for you.
Languages
Frameworks
As a ML engineer, I bridge the gap between data scientists, data engineers and devops engineers.
I help you on the following tasks :
Frameworks
Recommendations
Samuel K.
Air Liquide - Product Line Manager Datalake
Cyril à été d'une très grande aide dans la réalisation de notre projet d'API data. Il a mis en place toute la stack technique en IaC, du développement à la production ainsi que l'implémentation à partir de la spécification fonctionnelle et au passage le pipeline d'alimentation des données avec les transformations métier. Aujourd'hui elle est déjà utilisée par plusieurs applications. Cyril est déterminé et efficace dans son travail et sait communiquer. Il est un vrai atout pour toute équipe. Je recommande et espère pouvoir travailler de nouveau avec lui.
Alexandre J.
Medissimo - Head of product
Cyril est intervenu chez Medissimo pour mettre en place un module analytique utilisant nos bases de données. En amont de la mission, il nous a conseillé sur la solution la plus adaptée, et a su l'intégrer efficacement à nos infrastructures existantes. Cyril a aussi réalisé une formation en présentiel sur des méthodes et bonnes pratiques data qui ont débloqué et facilité un projet de back-office. Cyril connaît son sujet et c'est avec plaisir que nous retravaillerons avec lui.
Victor H.
ManoMano - Senior Growth Engineer
Cyril nous a rejoint deux semaines pour automatiser un traitement de données CRM via Python/Airflow. En s'adaptant très rapidement à nos outils ainsi qu'à nos process, il a su délivrer chaque échelon du livrable dans les temps. Les décisions techniques furent par ailleurs facilitées par une communication fluide et agréable. C'est avec plaisir que nous retravaillerions avec Cyril.
Jonathan B.
Simudyne - COO
Cyril enthusiastically approaches complex problems and is able to think through them clearly. He is a good listener and is able to explain complicated ideas succinctly to team members on the business and technical sides. Cyril was also involved in some presentations to partners and clients where he represented the company very well. Cyril is a promising machine learning engineer and I would gladly work with him again in the future.
Azam A.
Gumgum - Senior data engineer
At Gumgum, Cyril was working with me on data-engineering and backend development. He started as an intern, and quickly showed great aptitude and a drive for results. Eventually becoming a full time member of the team, he consistently produced results and became a key asset. I would work with him again and recommend him to any software engineering or data related role.
Antoine W.
MyTraffic - Senior software engineer
J'ai eu le plaisir de travailler avec Cyril sur des projets de data engineering pendant 3 mois à MyTraffic. Ca a été un plaisir: Cyril est à la fois curieux et rigoureux, il vise la perfection tout en gardant les impératifs business en tête. Il n'a jamais hésité à "mettre les mains dans le cambouis" et à monter en compétences sur certaines parties du produit moins axées data engineering. Et en bonus: il est super sympa ! Je suis convaincu que, grâce à ses qualités ainsi que ses capacités de raisonnement et de communication, Cyril saura relever tout défi tech qui se présente à lui.
Latest work
Here are some examples of projects I worked on, in various contexts (start-ups, bigger companies, independently, as an employee).
At ManoMano, I designed the architecture of an MLOps platform on AWS, then implememented and industrialized for all the data teams in the company. It is currently used daily by the data science team for building, deploying and monitoring ML models.
I teach data courses, trainings in schools and companies (Model deployment, data science, data engineering, CI/CD, best practices in data)
At MyTraffic, I implemented data science models at high scale, and deployed them on the cloud for pedestrian traffic insights.
Built and maintained batch and real-time data pipelines to provide business insights on a continuous basis. These pipelines were downstream from a programmatic ad-serving platform generating 50 TB of data a day.
Deployed a suite of monitoring and management tools across multiple Kafka clusters. These tools reduced the engineering time of certain cluster operations (scaling, rebalancing) by 90% as well as enhanced the overall visibility into the health of these clusters.
![Thumbnail [100%x225]](assets/lays.pro/img/portfolio/gumgum-forecasting.png)
Developed a high-scale programmatic inventory forecasting web tool. This tool uses an ARIMA model and terabytes of historical data to predict ad inventory. In close cooperation with operational teams, we provided the end-users the ability to determine achievable ad campaigns goals with confidence using the forecast results.
![Thumbnail [100%x225]](assets/lays.pro/img/portfolio/inference-api-screenshot.png)
A simple computer vision system able to classify images into 1000 object categories, such as keyboard, pencil, and many animals. Visit the UI or try it out below.
Deeplabv3+
DeepLab is a state-of-art deep learning model for semantic image segmentation, where the goal is to assign semantic labels (e.g., person, car, dog, bicycle and so on) to every pixel in the input image.
DeepLabv3+, extends DeepLabv3 by adding a simple yet effective decoder module to refine the segmentation results especially along object boundaries.
According to Papers With Code, it has the best accuracy and is the current state of the art on the Pascal VOC dataset.
The code is available here.
Try it out !
Or send one of the sample images...
