Director, Machine Learning Operations Engineering
Description For Director, Machine Learning Operations Engineering
Early Warning Services, a leading financial technology company known for products like Zelle® and Paze℠, is seeking a Director of Machine Learning Operations Engineering to lead their ML infrastructure and operations team. This senior-level position offers a competitive salary range of $190,000-$250,000 depending on location, with comprehensive benefits including unlimited PTO for exempt employees.
The role requires a seasoned professional with 12+ years of experience in ML Engineering or ML Ops, combining technical expertise with leadership capabilities. You'll be responsible for leading a team of ML Ops Engineers while developing and implementing strategic direction for the company's ML infrastructure. The position involves designing and maintaining scalable ML pipelines, optimizing deployment processes, and ensuring robust monitoring systems for model performance.
The ideal candidate will possess expert-level Python programming skills, deep AWS experience, and proficiency with modern ML tools and containerization technologies. You'll work in a hybrid environment across multiple office locations (Scottsdale, San Francisco, Chicago, or New York), collaborating with data scientists and software engineers to streamline the ML lifecycle from development to production.
Early Warning Services offers an excellent benefits package including comprehensive healthcare, 401(k) with 100% company match up to 6%, unlimited PTO for exempt employees, and 12 weeks of paid parental leave. The company's focus on financial technology and its crucial role in the U.S. financial system makes this an exciting opportunity for someone looking to make a significant impact in the fintech sector.
This role represents a unique opportunity to lead ML operations at a company that processes hundreds of millions of transactions and protects the U.S. financial system. You'll be at the forefront of implementing cutting-edge ML solutions while building and mentoring a team of technical professionals. The position offers both technical challenges and leadership opportunities, making it ideal for an experienced ML professional ready to take on a strategic role.
Responsibilities For Director, Machine Learning Operations Engineering
- Lead team of ML Ops Engineers and manage day-to-day backlog
- Develop strategic direction for ML Ops team, platform, and infrastructure
- Design, build, and maintain scalable ML infrastructure and pipelines
- Optimize orchestration processes for model deployment
- Monitor and maintain ML infrastructure performance and security
- Collaborate with data scientists and software engineers
- Develop tools for data analysis and model versioning
- Create robust monitoring systems for model performance
- Develop automation scripts and tools
- Provide technical assistance and mentorship
Requirements For Director, Machine Learning Operations Engineering
- Bachelor's degree in Computer Science, Engineering, or related field
- 12+ years experience in Data Science, ML Engineering or ML Ops capacity
- 5 years experience managing highly technical employees
- Expert level programming skills in Python and experience with Data Science and ML packages
- Deep experience with AWS services and architecture
- Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD practices
- Experience with MLOps tools such as MLflow, Kubeflow
- Expert understanding of data management and software architecture principles
- Experience in hybrid (OnPrem / Cloud) environments
- Hadoop / Hive / Cloudera experience
- Experience with Scala / Java programming languages and Spark
Benefits For Director, Machine Learning Operations Engineering
- Healthcare Coverage (PPO/HDHP)
- Dental and Vision Insurance
- 401(k) with 100% Company Match up to 6%
- Unlimited Time Off for Exempt employees
- 11 paid company holidays
- 12 weeks of Paid Parental Leave
- Maven Family Planning Support
- Health Savings Account (HSA)
- Flexible Spending Accounts (FSA)
- Paid volunteer day
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