Lead the design, development and deployment of Machine Learning models to solve business problems.
Develop and maintain clean, efficient, and scalable code that meets industry standards.
Analyze large datasets to extract actionable insights and make informed decisions.
Employ state-of-the-art Machine Learning methodologies and frameworks to develop robust and scalable models.
Influence technical direction and take ownership of key components of systems and solutions, ensuring that they meet the needs of the business.
Collaborate with key stakeholders in the development of data-driven solutions and deployable products.
Mentor and guide team members to help establish team domain expertise.
Contribute to the company’s intellectual property and technical leadership through patents and publications at top-tier conferences and journals.

7+ years of industry experience in applied Machine Learning
Graduate Degree in CS/ML or a related field
5+ years experience in building, deploying, and managing machine learning and deep learning models in production environments at scale
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
Experience in at least two of these domains: natural language processing, computer vision, fraud detection and authentication.
Extensive experience in scientific libraries in Python (numpy, pandas) and Machine Learning tools and frameworks (Scikit-Learn, 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

Staff Applied Scientist

Key skills