Software Engineer, Machine Learning Infrastructure

Posted 2024-10-18

💎 Seniority level: Middle, 3-5 years

📍 Location: US, Canada

🔍 Industry: Financial infrastructure

🗣️ Languages: English

⏳ Experience: 3-5 years

🪄 Skills: Backend DevelopmentPythonSoftware DevelopmentArtificial IntelligenceJavaMachine LearningCollaboration

3-5 years of experience building software applications in large scale distributed systems.
Strong curiosity and a desire to learn and share knowledge in a collaborative environment.
Solid engineering background and experience with infrastructure or distributed systems, primarily using Python and Java.
Familiarity with the full life cycle of software development from design to deployment.
Experience building and maintaining high availability, low latency systems.
Pragmatism in deciding between ideal solutions and necessary adjustments.

Building powerful, flexible, and user-friendly infrastructure that powers all of ML at Stripe.
Designing and building fast, reliable services for ML model training and serving across multiple regions.
Creating services that enable ML engineers to seamlessly transition from experimentation to production.
Pairing with product teams and ML engineers to develop easy-to-use infrastructure for production ML models.

Posted 2024-11-07

📍 United States, Canada, Philippines

🧭 Full-Time

💸 202300 - 308000 USD per year

🔍 Home services platform

🏢 Company: Thumbtack

8+ years of engineering experience with significant focus on distributed systems.
4+ years of hands-on experience building ML infrastructure or ML platforms at scale.
Deep expertise in at least one major programming language; proficiency in our core stack (Go, Python) preferred.
Proven track record of technical leadership on complex, cross-functional projects.
Strong architectural skills with experience designing scalable, reliable distributed systems.
Deep understanding of ML workflows, common frameworks, and operational challenges.
Experience mentoring teams and driving engineering excellence.
Track record of making strategic technical decisions with organization-wide impact.

Define and drive the technical vision and architecture for Thumbtack's next-generation ML infrastructure.
Lead cross-functional initiatives spanning engineering, data science, and product teams to build scalable, enterprise-grade ML systems.
Architect and oversee implementation of critical ML infrastructure components including model serving systems and RAG systems that can scale.
Establish technical standards and best practices for ML engineering across the organization.
Mentor and provide technical leadership to engineering teams on ML infrastructure best practices.
Partner with senior leadership to align ML infrastructure capabilities with business objectives.

LeadershipPythonMachine LearningPyTorchStrategyData scienceGoTensorflowMentoring

Posted 2024-11-07

🔧 Requirements