Tech Lead Manager, Model Integration

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Tech Lead Manager, Model Integration based in United States. This role offers the opportunity to lead a highly skilled engineering team focused on bringing machine learning models from development into reliable, production-ready systems. You will combine technical leadership, platform engineering expertise, and people management to build scalable model integration capabilities. The position sits at the intersection of AI, software infrastructure, and advanced technology development. You will define technical direction, improve engineering workflows, and enable faster, safer deployment of intelligent systems. Working closely with cross-functional engineering teams, you will solve complex integration challenges and create tools that improve productivity and reliability. This is an impactful leadership role for an engineer passionate about AI systems, automation, and building high-performing teams. \n Accountabilities: The Tech Lead Manager, Model Integration will drive the technical vision, execution strategy, and team development required to scale machine learning integration capabilities. This role requires a balance of hands-on technical guidance, strategic planning, and leadership across complex engineering initiatives. Lead, mentor, and grow a team of engineers responsible for integrating machine learning models into large-scale production software systems. Define the technical roadmap for model integration platforms, focusing on scalability, reliability, automation, and developer productivity. Build and improve tools, workflows, and platforms that enable efficient movement of models from development environments into simulation, validation, testing, and production. Collaborate with machine learning engineers, infrastructure teams, software platform groups, and technical leaders to ensure effective model integration and deployment. Improve model onboarding, configuration management, interface consistency, observability, and release readiness throughout the integration lifecycle. Identify opportunities to automate processes, reduce operational bottlenecks, and improve engineering efficiency. Establish strong engineering standards around quality, validation, governance, testing, and operational excellence. Partner with leadership teams to prioritize initiatives, manage dependencies, and deliver strategic technical milestones. Provide coaching, performance feedback, and career development support to engineers while fostering an inclusive and high-performing team culture. Contribute to hiring efforts and strengthen engineering practices across the organization. Requirements: The ideal candidate is an experienced engineering leader with a strong background in machine learning systems, software platforms, and scalable infrastructure. They combine technical depth with strong communication skills and the ability to guide teams through complex technical challenges. 8+ years of experience in machine learning systems, software infrastructure, platform engineering, deployment systems, or related large-scale software environments. Strong software engineering expertise with hands-on experience in Python and at least one systems programming language such as C++. Experience building or operating internal platforms, workflow automation systems, configuration frameworks, release tooling, or developer infrastructure. Proven experience integrating machine learning models or complex software components into production environments. Strong understanding of software quality, validation, observability, reliability, and production operations. Experience developing and debugging software in Linux-based environments. Demonstrated success leading technical teams or managing large cross-functional engineering initiatives. Strong stakeholder management and communication skills, with the ability to align diverse technical teams around shared goals. Experience with autonomous systems, robotics, advanced driver assistance technologies, or real-time machine learning applications is a plus. Familiarity with machine learning deployment pipelines, model packaging, inference workflows, governance processes, and release management practices is preferred. Experience building self-service engineering platforms that improve speed, consistency, and quality. Ability to apply AI-assisted tools and workflows to improve software development and engineering productivity. Strong ability to navigate ambiguity, create alignment, and translate complex technical challenges into practical solutions. Benefits: Competitive annual salary range of $218,800 - $335,300 USD, depending on experience, location, skills, and qualifications. Performance-based incentive compensation opportunities. Comprehensive health and wellbeing benefits, including medical, dental, and vision coverage. Health Savings Account (HSA) and Flexible Spending Account (FSA) options. Retirement savings plans and financial wellness programs. Life insurance, disability coverage, and employee assistance programs. Paid vacation, holidays, and time-off benefits. Tuition assistance and opportunities for professional development. Employee vehicle discount programs and access to company vehicle evaluation opportunities where applicable. Opportunity to work remotely within the United States while contributing to innovative AI and software initiatives. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1