Machine Learning Engineer, Qloo
LLM / Personalization
AI-powered recommendation API
Be an early applicant
AI-powered recommendation API
21-100 employees
Be an early applicant
21-100 employees
Company mission
To demystify the intricacies of global tastes and preferences.
Role
Who you are
- 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
What the job involves
- 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
- 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
Our take
Powered by AI, Qloo is aiming to understand taste and cultural correlations. While giants like Spotify, Expedia and Netflix dominate their sectors, they inadvertently create "data silos", where valuable information remains isolated. A unified system, however, could help understand and predict diverse personal tastes across various domains.
To confront this, Qloo provides companies with AI-generated correlation data spanning numerous cultural and entertainment domains. Leveraging its platform, a user's taste in one category or genre can seamlessly inform recommendations in another, leading to more personalized experiences. For example, Starbucks is using Qloo to create in-store music playlists tailored to specific neighborhoods, enhancing customer engagement.
With an influx in funding over 2023 and 2024, Qloo is now introducing an accessible self-service interface, aiding small and mid-sized enterprises in charting consumer and taste analytics. Additionally, it has introduced the "multi-person recommendation AI", capable of matching profiles based on individual preferences stored in its database, which further solidifies its position as a leader in personalized recommendation solutions.
Steph
Company Specialist at Welcome to the Jungle
Company
Company benefits
- Champion your health: We offer 100% health insurance coverage, with the ability to join group dental and vision for a nominal fee.
- Invest in your future: Qloo’s competitive 4% 401K matching program helps you build a financial foundation for the years ahead.
- Generous PTO: With 20 days of PTO and 10+ annual company holidays, we encourage taking time to rest and investing in your life outside of work.
- Thrive in Soho: Our sun-lit, spacious office in Soho boasts standing desks, team lunches every Thursday, monthly outings, and a tight-knit community of hard workers.
- Parental Leave: Whether you’re welcoming a child through birth or adoption, Qloo supports all new parents with three months of paid parental leave.
- Ownership Mentality: We provide stock options to all positions, ensuring that everyone, regardless of level, has a stake in our success and shares in our achievements.
Company HQ
SoHo, New York, NY
Leadership
Alex Elias
(Founder & CEO)Previously served as a Principal at APE Capital for 4 years before founding Qloo in 2012.
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