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Remote Music Curator Jobs (NOW HIRING)

Associate Solutions Engineer

New York, NY · On-site +1

$73K - $105K/yr

... music artists, media, brands, and more, plus a globe-spanning consumer behavior and sentiment ... From understanding global travel trends to curating the perfect restaurant recommendation based on ...

Remote Music Curator information

See salary details

$25.5K

$72.6K

$119.5K

How much do remote music curator jobs pay per year?

As of Jun 8, 2026, the average yearly pay for remote music curator in the United States is $72,627.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $94,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Remote Music Curator position, and why are they important?

To thrive as a Remote Music Curator, you need a deep understanding of music theory, genres, and trends, often supported by experience in music selection or a relevant degree. Familiarity with digital music platforms, playlist management tools, and audio editing software is essential. Strong communication, creativity, and attention to detail help curators craft engaging playlists and collaborate virtually with other team members. These skills enable curators to deliver tailored musical experiences that resonate with diverse audiences and meet client or platform expectations.

What are the typical daily responsibilities of a Remote Music Curator?

A Remote Music Curator typically spends their day discovering and evaluating new music, designing playlists for various audiences or moods, and analyzing user engagement data to refine their selections. They may also collaborate with other curators, artists, or marketing teams through video calls and project management tools. Additionally, they stay current with emerging trends in music and respond to feedback from listeners or clients. This dynamic routine lets curators balance creative discovery with data-driven decision-making, making the role both engaging and impactful.

What is a Remote Music Curator job?

A Remote Music Curator is responsible for selecting, organizing, and maintaining playlists or music libraries for streaming platforms, brands, or media companies. They analyze trends, consider audience preferences, and ensure that the music aligns with a specific mood, theme, or brand identity. This role often involves researching new music, collaborating with artists or labels, and using data analytics to optimize playlists. Since the job is remote, curators work from anywhere with an internet connection and typically communicate with clients or teams online.

More about Remote Music Curator jobs
What cities are hiring for Remote Music Curator jobs? Cities with the most Remote Music Curator job openings:
What are the most commonly searched types of Music Curator jobs? The most popular types of Music Curator jobs are:
What states have the most Remote Music Curator jobs? States with the most job openings for Remote Music Curator jobs include:
What job categories do people searching Remote Music Curator jobs look for? The top searched job categories for Remote Music Curator jobs are:
Machine Learning Engineer (LLM / Personalization)

Machine Learning Engineer (LLM / Personalization)

Qloo

New York, NY • On-site, Remote

$100K - $120K/yr

Full-time

Medical, Retirement, PTO

Posted 25 days ago


Job description

About Us

At Qloo, our cutting-edge Taste AI technology leverages extraordinary amounts of data-over half a billion records of public figures, places, music artists, media, brands, and more, plus a globe-spanning consumer behavior and sentiment database-to unearth deep insights about consumer preferences.

From understanding global travel trends to curating the perfect restaurant recommendation based on your unique tastes, our Taste AI engine sifts through the noise to find the signals that matter.

And the best part? Qloo's API suite is powered by cultural entities, not personal identities-ensuring our insights are derived without relying on personally identifiable information.

As we expand our investment in LLMs and AI agents, we are building the next generation of intelligent systems that combine generative models with structured taste intelligence-bringing reliability, explainability, and real-world grounding to AI applications.

Role Overview

As a Machine Learning Engineer reporting to the LLM Research Lead, you will operate at the intersection of large language models, recommendation systems, and Qloo's proprietary taste graph.

You will work closely with Research and Data Engineering teams to design and deploy systems that integrate LLMs with structured cultural intelligence. This includes building production-ready ML systems, experimenting with new model architectures, and developing novel approaches to grounding generative AI in real-world data.

This role is ideal for someone who enjoys both research-adjacent work and shipping production systems-and wants to shape how LLMs interact with structured knowledge at scale.

Responsibilities
  • Design, build, and deploy machine learning models and systems that power personalization, recommendation, and taste understanding
  • Develop and productionize LLM-powered features, including retrieval-augmented generation (RAG), agent workflows, and prompt / tool orchestration

  • Integrate LLMs with Qloo's structured entity graph and embedding systems to improve accuracy, relevance, and explainability

  • Experiment with and evaluate modern ML approaches (transformers, embedding models, ranking systems, hybrid recommenders)

  • Collaborate with Data Engineering to leverage large-scale datasets for LLM pipelines

  • Contribute to model evaluation frameworks and optimize model performance, cost, and latency in production environments

  • Stay up-to-date with the latest advancements in LLMs, recommendation systems, and applied ML-and bring those insights into production

Qualifications
  • Strong experience in Python and machine learning frameworks (e.g., PyTorch, CUDA, Metaflow/Kubeflow, etc)

  • Experience working with large language models (LLMs), including APIs (OpenAI, Anthropic, etc) and/or open-source models (Hugging Face)

  • Familiarity with retrieval systems, embeddings, vector search, or recommendation systems

  • Experience building and deploying ML systems in production environments

  • Solid understanding of data pipelines (Airflow) and working with large-scale datasets (e.g., Spark, S3, SQL)

  • Experience with AWS or similar cloud platforms

  • Experience working in AI-native development workflows, including heavy use of tools like Claude Code, Cursor, or similar

  • Strong problem-solving skills and ability to work across both research and engineering domains

  • Prior experience in a startup or fast-paced environment

We Offer
  • Competitive salary and benefits package, including health insurance, retirement plan, and paid time off
  • The opportunity to shape how LLMs and structured data systems work together in real-world applications

  • A collaborative, low-ego work environment where your ideas are valued and your contributions are visible

  • Direct exposure to cutting-edge work at the intersection of generative AI and large-scale recommendation systems

  • Flexible work arrangements (remote and hybrid options) and a healthy respect for work-life balance

$100,000 - $120,000 a year
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.
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