Tech Lead Model Integration
Job Summary
The Tech Lead Manager for Model Integration will lead and grow a team focused on transforming machine learning models into production-ready software. This role involves setting technical direction for integration workflows and fostering a collaborative, high-performing engineering culture. The position requires a leader experienced in machine learning systems to bridge the gap between development and scalable production deployment.
Responsibilities
- Lead and mentor a team of model integration engineers
- Develop roadmaps for integration scalability and automation
- Design platforms to streamline ML deployment lifecycles
- Establish engineering standards for quality and governance
Required Skills
- 8+ years in ML systems or platform engineering
- Proficiency in Python and C++
- Experience with production ML deployment pipelines
- Expertise in Linux-based development environments
Job Details
### Responsibilities
- Lead, mentor, and grow a team of engineers focused on integrating machine learning models into large-scale production software systems.
- Set the technical direction and roadmap for model integration workflows, with a focus on scalability, reliability, automation, and developer productivity.
- Drive the design and development of tools, platforms, and processes that simplify how models move from development into simulation, testing, and production environments.
- Partner closely with machine learning engineers, infrastructure teams, software platform teams, and program leaders to ensure models can be integrated, validated, and released efficiently.
- Improve model onboarding, configuration, interface management, observability, and release-readiness processes across the integration lifecycle.
- Identify and remove bottlenecks in model integration workflows by reducing manual steps and increasing automation.
- Establish strong engineering practices for quality, validation, governance, and operational excellence.
- Work with engineering leadership and program management to define priorities, align dependencies, and deliver key milestones.
- Conduct performance reviews, provide coaching and feedback, and support engineers in their growth toward senior technical or management roles.
- Foster an inclusive, collaborative, and high-accountability team culture.
### Required Qualifications
- 8+ years of experience in machine learning systems, software infrastructure, platform engineering, deployment systems, or related large-scale software domains.
- Strong software engineering skills with hands-on experience in Python and at least one systems programming language such as C++.
- Experience building or operating internal platforms, workflow automation, configuration systems, release tooling, or developer-facing infrastructure.
- Experience integrating machine learning models or complex software components into production systems.
- Strong understanding of software quality, validation, observability, and reliability in production environments.
- Experience developing and debugging software in Linux-based environments.
- Demonstrated success leading technical teams or driving large cross-functional initiatives with measurable business or engineering impact.
- Strong communication and stakeholder management skills.