Senior Machine Learning Engineer

Details of the offer

? WHO WE ARE

Adikteev, a member of the 2023 "French Tech 120," fuels the app ecosystem by inspiring users to engage with the apps they know and love.
Specializing in user retention, we grow in-app revenue and build user loyalty with custom retargeting and churn prediction campaigns.
With over 100 employees and offices in Paris, San Francisco, and Seoul, Adikteev operates worldwide, achieving a 60% revenue growth this year ($50m+ revenues in 2023).
? HOW WE DO IT ? Own It, Live It: Our top priority is making sure our customers are not just happy but thrilled.
We're not afraid to make bold moves, take charge of challenges, and see them through to the end.
? Rolling with the Changes: We don't just face challenges, we predict them.
Agility is our middle name, and we're all about continuous learning.
Adaptability is our recipe for success.
? Making Waves with Purpose: We're here to make a difference.
Every decision and action we take is aimed at making a meaningful impact.
? The ADIKTEAM Vibe: It's not just a team; it's the ADIKTEAM.
Each one of us is a crucial part of the squad and we're always on the lookout for A+ players.

? WHAT YOU WILL DO Your responsibilities will include:
Design, deploy, monitor, maintain, and improve machine learning and deep learning models in production.
Collaborate with the Engineering team to meet these objectives.
Our models serve diverse needs such as user conversion, churn prediction, app recommendation, and user segmentation.
These models have been developed and refined over the years to optimize performance while addressing key industry constraints like inference time and data volume.
Conduct custom analyses to provide insights for various stakeholders.
Examples include investigating performance shifts, A/B testing, evaluating business potential, and presale analysis.
? WHO YOU ARE You would be a good fit for the CTV team at Adikteev if you meet the following criteria:
Academics: Possess a strong theoretical background in mathematics and statistics.
Demonstrate significant mathematical and statistical credentials (A PhD in a relevant field is a plus but is not mandatory)
Experience: Have at least 2 years of hands-on experience in machine learning or in roles that leverage data science to power core company products or services.
For a Senior position, 5 years of hands-on experience are required.
Experience in Ad Tech is a plus.
Practical experience deploying models to production is required.
Experience with large-scale prediction systems is a plus.
Technical Skills: Proficiency in Python with coding best practices (e.g., clean code, typing, testing, vectorization and factorization).
Excellent command of core libraries like pandas, numpy, scipy, scikit-learn, and pytorch.
Experience with PySpark is a plus.
Excellent knowledge of database languages (SQL).
Experience with deployment to production environments.
Familiarity with AWS tools such as S3, EC2, EMR, Glue, and SageMaker is an advantage.
Mathematical Skills: A strong grasp of theoretical concepts in probability, statistical learning, and optimization.
Machine Learning Skills: You will need to be familiar with both tabular machine learning and deep learning techniques.
While our simplest models and data exploration tasks will require classic machine learning techniques, you will also be expected to master feature embedding and modern neural network architectures like transformers to develop state of the art models.
Expertise in querying, structuring, and processing qualitative or quantitative data to derive actionable business insights.
Knowledge of a variety of machine learning techniques and an understanding of their practical advantages and limitations.
Communication Skills: Speak and write clearly and concisely in English.
Fluency in French is a plus.
Please note that, for legal reasons, candidates are required to hold European citizenship and/or maintain residency within the European Union in order to be considered for this position. ? PERKS AND BENEFITS 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);
4 1/2 days work week (Fridays afternoon off);
"RTT";
50% of transportation fees covered by Adikteev (Navigo Pass);
Mental Health support;
Flexible remote working policy;
Regular team-life event / activity;
Parental leave Policy.
? OUR PROCESS HR call with Claire, Talent Acquisition Partner;
Case study to be completed remotely, followed by a restitution with Thomas, COO, and Gwennaëlle, Senior Data Scientist;
Final interview with Loïc, CPO and Thomas.
We prioritize people, not just job titles.

At Adikteev, we value talent in all its many forms and qualifications.
If, after reading this job description, you feel that the position aligns with your current abilities and career aspirations, we encourage you to apply even if you don't have every skill listed.

Not everyone will make it through our hiring process, but your skills might just be the perfect match for another adventure we have now or down the road.

As an Employer of choice, Adikteev does not and shall not discriminate on the basis of race, color, religion, gender, gender expression, age, national origin, disability, marital status, sexual orientation, or military status, in any of its activities or operations.
These activities include, but are not limited to, hiring and firing of staff, selection of volunteers and vendors, and provision of services.
We are committed to providing an inclusive and welcoming environment for all members of our staff, clients, volunteers, subcontractors, vendors and clients.

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Nominal Salary: To be agreed

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