Machine Learning Manager, Feed Ecosystems

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Manager, Feed Ecosystems based in United States.

This role offers the opportunity to lead a high-impact machine learning team focused on building next-generation recommendation systems. You will shape the technical strategy behind personalized content discovery, community growth, and ecosystem health at global scale. The position combines people leadership, advanced ML expertise, and cross-functional collaboration across product, engineering, data, and safety teams. You will guide the development of AI-powered systems that improve relevance, discovery, and meaningful user experiences. This is an opportunity to influence how millions of users discover content while balancing personalization, quality, and responsible AI practices. The ideal candidate is a strategic technical leader passionate about scalable ML systems and building strong engineering teams.

Accountabilities:: The Machine Learning Manager, Feed Ecosystems will lead a team of machine learning engineers responsible for developing recommendation and personalization systems that support user engagement, content discovery, and a healthy digital ecosystem. This role requires strong technical judgment, strategic thinking, and the ability to align complex ML initiatives with broader business and user goals.

Define the technical vision, strategy, and long-term roadmap for recommendation systems and feed ecosystem initiatives.

Lead, mentor, and develop a high-performing team of machine learning engineers, fostering technical growth and collaboration.

Oversee the design, development, deployment, and optimization of large-scale ML systems supporting personalization, discovery, and content distribution.

Partner with product, design, data science, safety, community, advertising, and infrastructure teams to identify opportunities and deliver impactful solutions.

Drive improvements in relevance for new, low-signal, and logged-out users through advanced modeling approaches.

Build systems that help new content and communities reach appropriate audiences while maintaining ecosystem quality.

Establish measurement strategies and quality signals that balance engagement, user value, contribution, and long-term community health.

Collaborate with platform and infrastructure teams to create scalable AI-powered solutions.

Ensure operational excellence through strong standards for reliability, performance, efficiency, and responsible AI development.

Support recruiting efforts to attract and hire exceptional machine learning talent.

Requirements:

The ideal candidate is an experienced engineering leader with a strong background in machine learning, recommendation systems, and managing technical teams. They should be comfortable operating in ambiguous environments while translating complex technical challenges into scalable strategies.

2+ years of experience managing and developing high-performing machine learning or recommendation systems teams.

Deep experience building and operating large-scale production ML systems.

Strong expertise in recommender systems, personalization, ranking, candidate retrieval, value modeling, or content understanding.

Experience with cold-start modeling, recommendation algorithms, or LLM-powered recommendation applications is highly valuable.

Strong understanding of ML measurement strategies and ecosystem optimization.

Ability to define and communicate technical strategies across complex, cross-functional environments.

Strategic mindset focused on creating scalable, responsible, and user-centered AI solutions.

Strong leadership, communication, and collaboration skills with the ability to influence diverse technical and business stakeholders.

Passion for developing high-quality systems that create meaningful user experiences and sustainable platform growth.

Benefits:

Competitive base salary range of $253,300 - $354,600 USD depending on experience, skills, location, and other factors.

Eligibility for equity compensation through restricted stock units.

Comprehensive healthcare benefits and income replacement programs.

401(k) retirement plan with employer match.

Global benefit programs supporting workspace needs, professional development, and caregiving.

Family planning support and gender-affirming care.

Mental health and coaching benefits.

Flexible vacation policy and paid volunteer time off.

Generous paid parental leave.

Opportunity to lead impactful AI initiatives at global scale while working remotely.

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