10 days ago
Base Salary
$175k - $250k/yr
Responsibilities
- Architect and implement the full lifecycle of ML models from data ingestion to production inference.
- Engineer and automate large-scale data processing pipelines using tools like Spark and dbt.
- Own the MLOps framework for model training, versioning, and deployment.
- Implement sophisticated deployment strategies to ensure safe, zero-downtime releases.
- Leverage cutting-edge tools to maximize throughput and minimize latency.
- Collaborate with data scientists to develop and optimize models for low-latency serving.
- Define, provision, and manage cloud infrastructure using Terraform.
Requirements
- 5+ years of experience in a software, data, or ML engineering role.
- Strong proficiency in SQL.
- Experience building and orchestrating data pipelines using tools such as Spark and dbt.
- Understanding of infrastructure as code, including experience with Terraform.
- Proficiency with containerization and orchestration including Docker and Kubernetes.
- Hands-on experience with CI/CD tools and ML lifecycle tools.
- Experience with AWS and its core services.
- Understanding of modern ML models and deployment trade-offs.
- Experience with systems incorporating Graph Neural Networks and complex models.
- Commitment to the highest ethical standards.
Benefits
- Fully-paid health care benefits.
- Generous parental and family leave policies.
- Volunteer opportunities.
- Support for employee-led affinity groups.
- Mental and physical wellness programs.
- Tuition assistance.
- A 401(k) savings program with an employer match.