Senior AI Machine Learning Engineer

Aquent; New York (NY); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Skill is seeking a senior ML engineer to build production ML systems for content understanding, NLP, and multimodal signals. This remote role requires proximity to NYC, with occasional on-site days to collaborate in person.

You will partner with Product, Engineering, and Data Science to take models end-to-end—from problem framing and data orchestration to shipping and monitoring in production. Strong experience with high-throughput systems is essential, as is a hands-on approach to evaluation.

Qualifications

• Hands-on experience deploying ML systems in high-throughput production environments.
• End-to-end ML solutions from problem formulation to shipping and monitoring models in production.
• Experience with content classification, quality scoring, ranking signals, or abuse/spam detection across text, audio, video, or metadata.
• Experience with NLP, LLMs, retrieval systems, and multimodal ML.
• Experience with ML pipeline orchestration tools (Python, Ray, Flyte).
• Ability to design robust evaluation frameworks and quantify model performance.

Responsibilities

• Work with senior engineers on ML initiatives from ideation to productionization.
• Design, develop, and deploy ML systems and quality signals across hundreds of millions of content items using real-time and batch processing.
• Advance NLP, multimodal AI, and content intelligence with a focus on quality classification, ranking signals, and spam detection.
• Build, evaluate, and iterate on ML and LLM-powered solutions with prompting, retrieval systems, and orchestration approaches.
• Audit, refactor, and mature existing models and pipelines for production reliability, throughput, and scale.
• Define evaluation methodologies with golden datasets, precision/recall frameworks, offline benchmarking, and online experiments.
• Partner with Product Managers, Engineering Managers, Staff Engineers, and Data Scientists to influence technical strategy and roadmaps.

Skills

ML systems

End-to-end ML

Content classification

Quality scoring

Ranking signals

Spam detection

NLP

Multimodal ML

Vector databases

Python

Tools

Claude Code

Cursor

Ray

Flyte

Job description

Please note this role is REMOTE but you must be in or near NYC. There will be days you might need to go onsite periodically.

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 across our client, including AI and spam detection, kids content classification, entity linking and creation, and content quality ranking signals.

Working at the intersection of large-scale machine learning, pipeline engineering, 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. In this role, you will play a central part in taking models end-to-end—translating ambiguous content challenges into robust, production-grade quality signals.

What You’ll Do

• Work with other senior and staff engineers on machine learning initiatives from ideation, problem formulation, and prototyping through experimentation, deployment, and large-scale productionization.
• Design, develop, and deploy machine learning systems and quality signals that operate across hundreds of millions of content items using both real-time and batch processing architectures.
• Advance our clients capabilities in natural language understanding, multimodal AI, and content intelligence, with a focus on quality classification, ranking signals, and spam detection.
• Build, evaluate, and iterate on ML and LLM-powered solutions using modern prompting techniques, retrieval systems, and advanced model orchestration approaches.
• Audit, refactor, and mature existing early-stage models and pipeline foundations, optimizing them for production reliability, throughput, and scale.
• Define rigorous evaluation methodologies utilizing golden datasets, precision/recall frameworks, offline benchmarking, and online experimentation.
• Partner closely with Product Managers, Engineering Managers, Staff Engineers, and Data Scientists to influence technical strategy, roadmaps, and architectural trade-offs.

Who You Are

• You have solid, hands-on experience developing and deploying machine learning systems in high-throughput production environments.
• You have a demonstrated track record of owning ML solutions end-to-end—from initial problem formulation and data orchestration to shipping and monitoring models in production.
• You bring experience with content classification, quality scoring, ranking signals, or abuse/spam detection across text, audio, video, or metadata.
• You have deep experience with machine learning, deep learning, and modern AI technologies, with a pragmatic bias toward engineering execution and shipping impact.
• You have hands-on experience working with large language models, NLP, retrieval-augmented generation (RAG), vector databases, or multimodal ML systems, and know how to adapt them for real-world product challenges.
• You are comfortable diving into early-stage prototypes or existing codebases, making sound technical decisions on whether to iterate, optimize, or rewrite components from scratch.
• You have practical experience with ML pipeline orchestration and tooling (e.g., Python, Ray, Flyte) to independently construct, train, and maintain ML workflows.
• You have experience building robust evaluation frameworks and can quantify model performance through disciplined 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 are curious about emerging AI technologies and excited about integrating tools such as Claude Code, Cursor, and other AI-assisted capabilities into engineering workflows.

About Skill

Skill connects the best professional, IT, engineering, financial and administrative talent with the world’s biggest brands. Our eligible talent get access to benefits such as health benefit contributions, retirement plans with match and flexible spending accounts.

Skill is an equal-opportunity employer. We evaluate qualified applicants without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We’re about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.