Senior Machine Learning Specialist
About the opportunity:
The Senior Machine Learning Specialist plays a pivotal role in developing and deploying cutting-edge machine learning solutions for retail pricing that incorporates various customer and operational business constraints and translates complex real-world problems into well-defined mathematical objectives.
Minimum requirements include:
* A PhD or Master's degree in Computer Science, Machine Learning, Statistics, Operation Research, or a related field
* 5+ years of industry experience in applied machine learning, 3+ years experience in building, deploying, and managing machine learning and deep learning models in production environments at scale
Key skills and qualifications include:
* Deep understanding of ML best practices (A/B testing, training/serving pipelines, feature engineering etc), algorithms/techniques (gradient boosting, deep neural networks, optimization, regularization), and experiment design
* Proficiency with scientific libraries in Python (numpy, pandas, polars) and Machine Learning tools and frameworks (ScikitLearn, Tensorflow, Keras, PyTorch)
* Strong data engineering skills and experience working with large-scale datasets
* Experience with big data tools (Apache Beam, Apache Kafka, Spark)
* Experience with cloud technologies AWS, GCP or Azure - Fluency in Python, SQL
Preferred requirements include:
* PhD preferred (CS, ML, AI, Statistics, Operation Research or related field)
* Background in applying ML techniques to solve real-world business problems in the retail sector, especially pricing
* Familiarity with MLOps tools and pipelines
* Impact-focused and passionate about delivering high-quality models
* Demonstrated leadership experience, with the ability to lead and inspire a team
Interview : one-hour Python and SQL coding challenge.
Avenue Code is committed to maintaining confidentiality and adhering to global data protection laws, such as GDPR, LGPD, CCPA, and CPRA. Candidate data shared will be kept confidential and used solely for application purposes.
The ideal candidate should possess strong technical acumen, collaborative problem-solving abilities, and a warm professional demeanor.