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Qloo Jobs (NOW HIRING)

Qloo

Senior Backend Engineer - Platform

New York, NY · On-site

$145K - $165K/yr

About Us At Qloo, our cutting-edge Taste AI technology leverages extraordinary amounts of data-over half a billion records of public figures, places, and things, plus a globe-spanning consumer ...

Qloo

Senior Backend Engineer - Platform

New York, NY · On-site +1

$145K - $165K/yr

About Us At Qloo, our cutting-edge Taste AI technology leverages extraordinary amounts of data-over half a billion records of public figures, places, and things, plus a globe-spanning consumer ...

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Qloo information

What is the difference between Qloo vs Data Analyst?

AspectQlooData Analyst
Required CredentialsTypically a degree in data science, statistics, or related fieldUsually a degree in data science, statistics, or a related field
Work EnvironmentTech companies, entertainment, marketing, and consumer insights firmsBusiness, finance, healthcare, and technology sectors
Employer & Industry UsageUsed for consumer insights, recommendation systems, and market researchUsed for data interpretation, reporting, and strategic decision-making
Common Search & ComparisonQloo vs Data AnalystData Analyst roles and responsibilities

While both Qloo and Data Analysts work with data, Qloo focuses on consumer insights and recommendation algorithms, often within tech and entertainment industries. Data Analysts interpret data to inform business decisions across various sectors. The roles overlap in data handling and analysis skills but differ in application and industry focus.

How does a role at Qloo typically involve collaboration between data scientists, engineers, and product managers?

At Qloo, team members often work in cross-functional groups where data scientists, engineers, and product managers closely collaborate to develop and refine recommendation algorithms. Data scientists focus on analyzing cultural data and building predictive models, while engineers ensure these models are seamlessly integrated into Qloo’s platform. Product managers coordinate this work, gathering requirements and ensuring the solutions align with client needs. This collaborative structure fosters innovation and provides opportunities to learn from colleagues across disciplines.

What are the key skills and qualifications needed to thrive as a Data Scientist at Qloo, and why are they important?

To thrive as a Data Scientist at Qloo, you need a solid background in statistics, machine learning, and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Expertise in programming languages like Python or R, experience with data processing tools (such as SQL, Spark, or Hadoop), and familiarity with recommendation systems are commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help translate complex data insights into actionable strategies. These skills are crucial for delivering accurate, personalized recommendations and supporting client needs in a data-driven company like Qloo.

What is a Qloo and what do they do?

Qloo is not a job title, but rather a technology company specializing in artificial intelligence and data analytics. Qloo provides insights into consumer preferences and cultural trends by analyzing data across different industries, such as entertainment, hospitality, and retail. The company's platform helps businesses understand what their customers are likely to enjoy or purchase next, allowing for more personalized recommendations and marketing strategies.
What cities are hiring for Qloo jobs? Cities with the most Qloo job openings:
What states have the most Qloo jobs? States with the most job openings for Qloo jobs include:
What job categories do people searching Qloo jobs look for? The top searched job categories for Qloo jobs are:
Qloo jobs near you
Infographic showing various Qloo job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 50% Physical, and 50% Remote job distribution.
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 13 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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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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