Engineering Manager, ML & Optimization Systems

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Engineering Manager, ML & Optimization Systems in the United States.

This leadership role sits at the intersection of machine learning, operations research, and large-scale cloud engineering, driving the next generation of real-time dispatch optimization systems. You will lead a high-impact team of Data Scientists, ML Engineers, and Software Engineers focused on building intelligent, low-latency decisioning platforms that directly improve service efficiency and operational outcomes. The role combines hands-on technical leadership with strategic ownership of ML and optimization roadmaps, ensuring research models are transformed into production-grade systems. You will shape architecture for scalable cloud-native services, oversee MLOps pipelines, and define best practices for model deployment, monitoring, and experimentation. Working cross-functionally with Product, Operations, and Engineering, you will translate complex scientific insights into business-critical decisions. This is a highly visible role with direct influence on real-time systems that operate at national scale and impact millions of service events annually.

Accountabilities

* Lead, mentor, and develop a multidisciplinary team of Data Scientists, ML Engineers, and Software Engineers, fostering a high-performance and collaborative culture.

* Own delivery of the ML and optimization roadmap, including project planning, estimation, risk management, and execution within Agile/Scrum frameworks.

* Define and guide the scientific and algorithmic strategy for constrained optimization and machine learning-driven dispatch systems.

* Architect and oversee end-to-end cloud-native systems enabling real-time decision-making, batch/stream processing, and optimization algorithms.

* Establish and scale MLOps practices, including automated training pipelines, model validation, A/B testing, deployment, and monitoring.

* Drive operational excellence by managing system reliability, technical debt, incident response, and production performance optimization.

* Partner with cross-functional stakeholders to communicate technical trade-offs, operational insights, and strategic recommendations.

* Lead continuous improvement initiatives across platform performance, cost efficiency, and system scalability.

Requirements

* Bachelor’s degree in Computer Science, Data Science, Operations Research, Engineering, or a related quantitative field (Master’s preferred).

* 6+ years of experience in Data Science, ML Engineering, or Operations Research, with strong experience deploying models into production systems.

* 2+ years of experience in engineering or technical leadership roles managing ML/DS teams.

* Deep expertise in machine learning techniques (e.g., XGBoost, PyTorch, Transformers) and optimization methods (MIP, linear, stochastic optimization).

* Strong experience building real-time, low-latency systems in Python, SQL, and AWS-based cloud environments.

* Proven ability to design and operate MLOps pipelines using tools such as Airflow, SageMaker, or similar platforms.

* Experience with large-scale, 24/7 production systems and incident-driven operational environments.

* Strong background in system architecture, distributed systems, and data-driven decision-making.

* Excellent leadership, communication, and stakeholder management skills with the ability to influence across technical and non-technical teams.

* Experience with BI/analytics tools, data modeling, and emerging AI/ML technologies (e.g., LLMs, generative AI) is highly desirable.

Benefits

* Competitive compensation package with a national salary range of USD $180,000 - $230,000 per year.

* Comprehensive health, dental, vision, disability, and life insurance coverage.

* 401(k) retirement plan with employer match and tuition assistance programs.

* Flexible work arrangements and generous paid time off, including holidays and sick leave.

* Family support benefits, including parental planning assistance.

* Performance-based bonus and incentive programs.

* Professional development opportunities in advanced AI, ML, and optimization systems.

* Inclusive and collaborative culture focused on innovation, growth, and long-term impact.

* Travel support for onboarding and occasional onsite collaboration or company events.

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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.