Sr. Machine Learning Engineer

Position Overview:

We are seeking a motivated and enthusiastic Senior Machine Learning engineer to join our machine learning team. The ideal candidate will have some industry or academic experience in working on classification and optimization problems in the context of a larger software system. This person will have the opportunity to apply their knowledge to exciting multimodal data challenges, contributing to model development and data analysis aimed at improving predictions, reducing risk, and empowering consumers in the growing alternative finance market.

How you'll make an impact:

• Assist in the development and deployment of scalable models and tools using machine learning and optimization techniques, with guidance from senior team members.
• Collaborate with the data engineering team to gather and integrate data, creating valuable features.
• Participate in assembling large, complex data sets that meet business requirements.
• Contribute to the analysis of customer behavior and optimization of credit risk models.

What you'll need to succeed:

• MS or PhD in a quantitative field such as Statistics, Econometrics, Mathematics, Physics, Computer Science, or related quantitative discipline.
• BS in the fields described above will be considered if skill set and experience are robust
• 6+ years of experience in one or more of the following areas: machine learning, artificial intelligence, data mining, or related research.
• Proficiency with Python, Java, or other general-purpose programming languages.
• Familiarity with deep learning and traditional classification methods (e.g., Deep Neural Networks, Decision Trees, Random Forest).
• Proficiency and working knowledge of at least one major deep learning framework (e.g. PyTorch, Tensorflow)
• Sequence modeling (e.g.RNNs, Natural Language Processing techniques, Attention-Based Autoregressive models)
• Understanding of basic statistical analysis (e.g., Hypothesis testing, experimental design).
• Exposure to cloud services such as AWS, especially EC2 and S3.
• Basic SQL skills and experience with big data tools and frameworks like Hadoop, Spark, or CockroachDB skills 
• Familiarity with common computing environments (e.g., Linux, Shell Scripting).
• Willingness to learn and develop skills in automated workflows (e.g., Airflow, Jenkins) and distributed systems.