Machine Learning Engineer

Responsibilities

• Design ML models and large-scale ML systems for underwriting and portfolio management subject to business, risk, regulatory, and engineering constraints.
• Design systems that accelerate the development and deployment of new models.
• Experiment and iterate on ML models using tools including PyTorch and TensorFlow.
• Develop automated pipelines to train and evaluate models in offline and online environments.
• Integrate ML models into production systems and ensure scalability and reliability.
• Collaborate with product and strategy partners to propose, prioritize, and implement product features.
• Evaluate emerging ML and AI developments and turn innovative ideas into production solutions.

Requirements

• Bachelor’s degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field.
• At least two years of experience building and shipping ML systems in production.
• At least two years of experience with ML algorithms and model architectures, designing, training, and evaluating models, productionizing and deploying models at scale, orchestrating data pipelines and leveraging large-scale datasets, and solving business problems with deployed ML models.
• At least one year of experience with ML libraries and frameworks including PyTorch, TensorFlow, XGBoost, or Spark.
• At least one year of experience with deep learning, including transformers, test-time compute, or reinforcement learning.

Benefits

• 40 hours per week
• 50% telecommuting permitted
• Multiple positions available
• Equity, company bonus or applicable sales commissions/bonuses
• 401(k) plan
• Medical, dental, and vision benefits
• Wellness stipends