Senior AI/ML Engineer

Job Title: AI/ML Engineer

Positions Details:

W2

Level: Senior

Location: New York or Boston (in-office), or remote with working hours in Eastern Time

Job Description About the position The Euler squad sits within the Enrichment & Content Intelligence product area and is focused on helping  better understand audio, text, and visual content through machine learning. The team develops technologies that power experiences acrossincluding AI and spam detection, kids content classification, entity linking and creation, and more. Working at the intersection of large-scale machine learning and product innovation, the squad partners closely with Product, Engineering, and Data Science teams to build intelligent systems that improve how users experience content across the platform. What you’ll do Work with other senior and staff engineers on machine learning initiatives from ideation and prototyping through experimentation, deployment, and large-scale productionization. Design, develop, and deploy machine learning systems that operate across hundreds of millions of content signals using both real-time and batch processing architectures. Advance  capabilities in natural language understanding, multimodal AI, and content intelligence. Build and evaluate LLM-powered solutions using modern prompting techniques, retrieval systems, and advanced model orchestration approaches. Define rigorous evaluation methodologies including golden datasets, precision and recall frameworks, offline benchmarking, and online experimentation. Partner closely with Product Managers, Engineering Managers, Staff Engineers, and Data Scientists to influence technical strategy and roadmap decisions. Who you are You have solid experience developing and deploying machine learning systems in production environments. You have successfully delivered large-scale machine learning architectures operating on substantial datasets and high-throughput production systems. You have deep experience with machine learning, deep learning, and modern AI technologies. You have hands-on experience working with large language models and understand how to evaluate, adapt, and deploy them effectively for real-world product challenges. You have experience building evaluation frameworks and can quantify model performance through robust experimentation and measurement techniques. You know how to navigate ambiguity and make thoughtful technical trade-offs that balance product impact, scalability, and engineering quality. You have experience working with NLP, prompt engineering, retrieval-augmented generation (RAG), vector databases, or multimodal machine learning systems. You are curious about emerging AI technologies and excited about integrating tools such as Claude Code, Cursor, and other AI-assisted development capabilities into engineering workflows. Will this position directly or indirectly manage others? - No Provide the top 3 hard and soft skills required for this role - Hard Skills - Machine learning classification, Light data engineering for ML pipelines and ML research and multimodal systems (Python, Ray, Flight) Soft Skills - Close team collaboration, Innovation and exploring ambiguous problem spaces, and Self-awareness and accountability for end-to-end product outcomes Provide any skills or experience that are not required but nice to have - Advanced data engineering expertise to independently construct, train, and orchestrate ML pipelines without assistance. How do you see this role bridging the gap between daily project goals and the company's broader strategic mission, and where do you expect this person to have the most influence across the organization? - The role addresses the influx of low-quality, AI-generated content across the platform. Influence is open-ended, allowing the engineer to guide technical direction alongside a staff engineer. Are there any known obstacles they will face, such as legacy systems, resource constraints, high-pressure deadlines, or complex stakeholder environments? - No legacy systems or rigid release deadlines exist. Navigating constant general pressure requires self-directed ML explor:

Location: New York or Boston (in-office), or remote with working hours in Eastern Time

AI Foundation develops the core ML and AI systems that power personalized experiences on  These systems rely on human judgment to ground their intelligence in the nuances of culture, personal taste, and real-world listening habits.