Senior Machine Learning Engineer
☆ Rolling with Changes : We don't just face challenges, we anticipate them. Agility is core to who we are, and we believe in continuous learning and improvement.
☆ Making waves with purpose : We're here to make a difference. Every decision and action is aimed at creating positive and meaningful impact.
☆ The ADIKTEAM vibe : We're more than a team; we're the ADIKTEAM. Everyone plays a crucial role, and we're always looking for people who thrive in collaborative, supporting environments. ☆ WHAT YOU WILL DO We are seeking a skilled Machine Learning Engineer who is passionate about building impactful solutions and thrives in a collaborative environment. If you enjoy solving complex challenges, sharing knowledge, and making a difference with data, we encourage you to apply. Your responsibilities will include:
- Design, deploy, monitor, maintain and improve machine learning and deep learning models in production . You will collaborate with the Engineering team for these purposes. Currently, our models serve diverse needs (user conversion, churn, app recommendation, user segmentation...). 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...).
- Support the professional development of a junior Machine Learning Engineer
- 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)
- Have at least 5 years of hands-on experience in machine learning or in roles that leverage data science to power core company products or services.
- Experience in Ad Tech is a plus.
- Practical experience deploying models to production is required.
- Experience with large-scale prediction systems is a plus.
- 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.
- A strong grasp of theoretical concepts in probability, statistical learning, and optimization.
- 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.
- 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
- Inclusive parental leave Policy.
- HR call with Claire, Talent Acquisition Partner ;
- Team fit interview with Loïc, Chief Product Officer ;
- Technical case study to be completed remotely with a follow-up discussion with Gwenaëlle and Nicolas, Senior ML Engineers ;
- Final interview with two executive committee members.
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