Senior Machine Learning Engineer, Recommendation in United States at Jobgether

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

This is an exciting opportunity for a highly skilled Machine Learning Engineer to shape the future of content discovery, personalization, and user engagement within a rapidly evolving consumer platform. In this role, you will design and optimize recommendation and search systems that directly influence how users discover, interact with, and consume content. Working at the intersection of machine learning, product development, and data science, you will build scalable systems that drive engagement, retention, and content distribution. The position offers significant ownership, allowing you to lead experimentation, develop advanced ranking models, and influence long-term machine learning architecture. Ideal for someone with strong technical expertise and product intuition, this role provides the chance to solve complex challenges in a fast-moving, AI-driven environment.

• Design, build, and continuously improve recommendation and search systems across content feeds, discovery experiences, search functionality, and content continuation features.
• Develop and optimize retrieval and ranking systems, including candidate generation pipelines, embedding-based retrieval, two-tower architectures, ranking models, and serving infrastructure.
• Lead end-to-end experimentation efforts, including hypothesis development, A/B testing, performance analysis, and iterative model improvements.
• Improve recommendation quality across key challenges such as cold-start users, newly created content, creator discovery, and rapidly evolving content ecosystems.
• Build user, creator, content, and session-level representations using behavioral, contextual, and engagement signals.
• Collaborate closely with Product, Data Science, and Engineering teams to define success metrics and deliver measurable improvements in engagement, retention, satisfaction, and content distribution.
• Develop production-grade machine learning systems with robust monitoring, evaluation, scalability, and reliability standards.
• Contribute to the evolution of long-term machine learning infrastructure and architecture supporting AI-native content discovery experiences.
• Translate user behavior patterns and complex datasets into actionable machine learning solutions that enhance product performance and user experiences.
• Stay current with emerging advancements in recommendation systems, ranking methodologies, retrieval techniques, and AI-powered personalization technologies.

• 5+ years of industry experience building and deploying production machine learning systems with significant ownership and technical leadership responsibilities.
• Proven experience developing recommendation engines, search systems, ranking models, feed optimization systems, advertising ranking platforms, or content discovery solutions.
• Strong background working on consumer-facing applications, particularly within social platforms, entertainment products, gaming ecosystems, creator platforms, or engagement-driven experiences.
• Hands-on expertise with retrieval and ranking architectures, including embedding-based retrieval, candidate generation, two-tower models, feature engineering, and relevance optimization.
• Strong understanding of online and offline evaluation methodologies, experimentation frameworks, and machine learning performance measurement.
• Excellent product intuition with a deep understanding of relevance, engagement, retention, satisfaction, personalization, and content distribution dynamics.
• Experience transforming large-scale behavioral data into meaningful machine learning signals and business outcomes.
• Solid engineering fundamentals, including data pipelines, backend integrations, distributed systems, production ML deployment, and model lifecycle management.
• Strong communication and collaboration skills with the ability to work effectively across technical and non-technical teams.
• High degree of ownership, adaptability, and problem-solving ability in fast-paced and ambiguous environments.
• Experience with semantic search, AI-powered recommendation systems, LLM-enhanced ranking, personalized content generation, or multimodal machine learning is considered a strong advantage.
• Familiarity with reinforcement learning, contextual bandits, explore/exploit strategies, long-term optimization frameworks, or user-generated content ecosystems is a plus.
• Startup experience or experience building machine learning systems from the ground up is highly desirable.

• Competitive compensation package with a market-leading salary and meaningful equity participation.
• Remote-first work environment offering flexibility and location independence.
• Comprehensive healthcare coverage and employee benefits package.
• Opportunity to work on cutting-edge AI, machine learning, and consumer technology challenges.
• High-impact role with ownership over critical product experiences affecting user engagement and growth.
• Collaborative environment with highly talented engineers, product leaders, and AI practitioners.
• Exposure to innovative technologies and emerging trends in recommendation systems and personalized content experiences.
• Fast-paced startup environment with opportunities for rapid professional growth and career advancement.
• Flexibility to explore new ideas, experiment with novel approaches, and contribute to long-term technical strategy.
• Inclusive and supportive culture focused on innovation, learning, and continuous improvement.