(Senior) Machine Learning Engineer
il y a 6 jours
Adikteev, a member of the 2022 "French Tech 120," fuels the app ecosystem by inspiring users to engage with the apps they know and love. With over 100 employees and offices in Paris, San Francisco, and Seoul, Adikteev operates worldwide, achieving an expected 60% revenue growth this year ($50m+ revenues in 2023)
★ Every decision and action we take is aimed at making a meaningful impact.
☆ Design, deploy, monitor, maintain and improve machine learning and deep learning models in production . You will collaborate with the Engineering team for these purposes. They have been developed and improved over the years to optimize their performances while taking into account the main constraints of our industry: inference time and data volume.
Perform custom analyses to give insights to various levels of stakeholders (investigate performance shift, A/B test, evaluate a business potential, presale analysis…).
Mentor a junior Machine Learning Engineer
★ You will be a good fit to join the Machine Learning team at Adikteev if you :
Hold a Master’s degree or PhD in STEM, preferably with a statistics focus.
Have 5+ years of experience working in teams using data science to power a core company product or service. Applied experience with machine learning on large datasets.
ML skills – Have proficiency in querying, structuring and processing qualitative or quantitative data to draw insightful business conclusions. You have knowledge of a variety of machine learning techniques and their real-world advantages/drawbacks.
Technical skills – Program deftly in Python (main packages: pandas, numpy, scipy, scikit-learn, tensorflow…) with coding best practices (clean code, DRY, typing, tests, formatting, factorization...). You have basic knowledge of database languages (SQL), competency in shell scripting, experience with deployment to Production and experience with AWS a plus (S3, EC2, EMR, Glue, SageMaker…).
Fluent English, French is a plus.
★ Competitive Salary ;
~ Performance-based Quarterly bonus with transparent KPIs;
~ Profit-sharing scheme ("Prime de participation") ;
~ Longevity bonus every 2 years ;
~ Healthcare plan with excellent coverage (50% of the contribution covered by Adikteev) ;
~€9 Lunch Vouchers (Tickets Restaurant - SWILE card - 50% of the contribution covered by Adikteev) ;
~Mental Health support ;
~ Flexible remote working policy ;
~ Parental leave Policy.
★ A hands-on use case to be completed remotely, followed by a restitution with Gwenaëlle, Senior Data Scientist and Thomas.
These activities include, but are not limited to, hiring and firing of staff, selection of volunteers and vendors, and provision of services.
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