20 days ago
Base Salary
$244k - $320k/yr
Responsibilities
- Design, build, and operate scalable machine-learning systems for real-time targeting, decisioning, and personalization.
- Own ML projects end to end from data exploration and modeling through deployment, monitoring, and iteration.
- Safeguard model and system quality through testing, monitoring, validation, and alerting.
- Collaborate with Product, Data, and Engineering partners to translate business problems into ML solutions.
- Improve system reliability, performance, and engineering efficiency.
- Contribute to technical direction and best practices across the ML engineering team.
- Mentor and support engineers through code reviews, design discussions, and knowledge sharing.
Requirements
- 6+ years of professional experience building production machine-learning software systems.
- Proven experience owning ML systems through the downstream impact of design decisions.
- Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or xgboost.
- Experience with pandas, Spark, SQL, and matplotlib for data processing and analytics.
- Hands-on experience building automated pipelines for data processing, model training, validation, and deployment.
- Experience collaborating with cross-functional teams to deliver ML-powered features.
- Strong communication skills and a high sense of ownership.
Benefits
- Competitive perks and benefits including health and wellness benefits and equity.
Tech Stack
Amazon DynamoDBApache AirflowApache SparkAWSCloudflareDatadogGradleGraphQLHelmIstioJavaKotlinKubernetesMatplotlibPandasPostgreSQLPythonPyTorchReactRedisSpring BootSQLTensorFlowTerraformTypeScriptXGBoost