Machine Learning Engineer
Build and productionize scalable machine learning models and systems for underwriting and portfolio management. The role requires a bachelor's degree and at least two years of experience shipping ML systems, plus expertise in model development, deployment, data pipelines, and deep learning.
About the job
Responsibilities
- Design state-of-the-art machine learning models and large-scale ML systems for underwriting and portfolio management, considering domain knowledge, risk, regulatory, and engineering constraints.
- Design systems that accelerate the development and deployment of new models.
- Experiment with and iterate on ML models using PyTorch and TensorFlow to achieve business goals and improve efficiency.
- Develop pipelines and automated processes 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.
- Monitor developments in ML and AI and translate 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 2 years of experience building and shipping ML systems in production.
- At least 2 years of experience with ML algorithms and model architectures; designing, training, and evaluating machine learning models; productionizing and deploying ML models at scale; orchestrating data pipelines and leveraging large-scale datasets; and building and deploying ML models to solve business problems.
- At least 1 year of experience with ML libraries and frameworks including PyTorch, TensorFlow, XGBoost, or Spark.
- At least 1 year of experience with deep learning, including transformers, test-time compute, or reinforcement learning.
Compensation and Benefits
- Base salary: $212,000–$318,000 per year.
- Equity, company bonus or sales commissions/bonuses may be available in addition to base salary.
- Benefits may include a 401(k) plan, medical, dental, and vision coverage, and wellness stipends.
- 40 hours per week.
- 50% telecommuting permitted.
Skills
Machine Learning, PyTorch, TensorFlow, Xgboost, Spark, Deep Learning, Transformers, Reinforcement Learning, Ml Algorithms, Data Pipelines, Large-Scale Datasets, Model Deployment, Production Ml Systems, Underwriting Models, Portfolio Management
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