RESPONSIBILITIES
- Develop, train, and optimize machine learning and statistical models for production use
- Build scalable data pipelines and model serving systems that support real time and batch workloads
- Collaborate with engineering teams to integrate models into APIs, services, and workflows
- Work with product and operations teams to understand user needs and translate them into ML solutions
- Conduct experimentation, evaluation, and validation using structured and unstructured data
- Improve performance, accuracy, and reliability of deployed models
- Maintain clear documentation for datasets, features, pipelines, and model behavior
QUALIFICATIONS
- 3 plus years of experience building and deploying machine learning systems
- Strong proficiency with Python and ML frameworks such as PyTorch or TensorFlow
- Experience with feature engineering, model evaluation, and applied statistics
- Familiarity with data pipelines, ETL tooling, or distributed data processing
- Understanding of model deployment practices and MLOps workflows
- Experience working with unstructured data such as text or documents
- Bonus experience with LLMs, embedding models, or retrieval augmented systems
- Bonus familiarity with AWS, containerization, or API development
WHO YOU ARE
- A practical ML engineer focused on solving real operational problems
- Comfortable working with ambiguity and translating requirements into reliable models
- Collaborative, curious, and driven to improve accuracy, speed, and system performance
EQUAL OPPORTUNITY STATEMENT
We are an equal opportunity employer and celebrate diversity, recognizing that diversity of thought and background builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
