Senior Machine Learning Scientist, Qloo
$140-180k
AI-powered recommendation API
Job no longer available
AI-powered recommendation API
21-100 employees
Job no longer available
$140-180k
21-100 employees
Company mission
To understand culture and taste on a global basis.
Role
Who you are
- If you're a proactive problem-solver with a passion for machine learning, we'd love to meet you
- 3+ years in a Machine Learning or ML Engineering role, with hands-on experience in deep learning frameworks (e.g., TensorFlow, PyTorch)
- A degree in Mathematics, Engineering, Statistics, Computer Science, Physics, or a related field. An advanced degree is highly preferred
- Proficient in Python and PySpark; experience with SQL or similar querying languages. Solid foundation in machine learning principles, including model evaluation, optimization, and deployment best practices
- Self-motivated, collaborative, and adaptable, with a "can-do" attitude and comfort in a fast-paced, often ambiguous environment
- Excellent communication and interpersonal skills, capable of bridging technical work with business applications
- Experience with model monitoring frameworks and A/B testing
- Familiarity with cloud environments (e.g., AWS, Google Cloud) and deployment of ML models at scale
- Exposure to startup or high-growth company environments
What the job involves
- Reporting to the Director of AI, this is a high-impact role where your expertise will directly shape the future of our ML/AI capabilities
- Our team values exploration and continuous learning, encouraging you to drive meaningful innovation and take on exciting challenges
- As an ML Scientist at Qloo, you will play a crucial role in developing and implementing cutting-edge machine learning models and data-driven solutions
- You will collaborate with cross-functional teams and work on a diverse range of projects, from data exploration and model development to the deployment and monitoring of machine learning systems
- Model Development & Deployment: Develop, test, deploy, and maintain machine learning models and algorithms, ensuring their scalability, robustness, and performance in production
- Data Analysis & Optimization: Conduct data preprocessing, feature engineering, and exploratory analysis to optimize AI/ML models
- Pipeline Development & Enhancement: Design, build, and enhance efficient machine learning pipelines, ensuring their scalability and performance
- Collaboration & Cross-functional Integration: Work closely with software engineers, data engineers, and other teams to integrate ML models into production systems, aligning with business requirements
- Model Performance Monitoring & Improvement: Implement tools for real-time model monitoring, evaluate performance, and drive continuous improvements to models and pipelines
- Experimentation & Innovation: Explore emerging ML techniques, deep learning methods, and advanced algorithms to enhance model capabilities and introduce new solutions
- Knowledge Sharing & Mentorship: Present findings to stakeholders (both technical and non-technical) and contribute to the development of best practices. Mentor junior team members and foster a collaborative team environment
- Continuous Learning: Stay current with industry trends and emerging technologies in data science and machine learning to identify new opportunities and techniques
Our take
Powered by artificial intelligence, Qloo is aiming to understanding 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 plans to introduce 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
- Health insurance, retirement plan, and paid time off
- Opportunities for professional development and growth
- A collaborative and supportive work environment where your ideas are valued and your contributions recognized
- Flexible work arrangements - we encouraging employees to maintain a well-rounded lifestyle
Company HQ
Bowery, New York, NY
Leadership
Alex Elias
(CEO)Previously served as a Principal at APE Capital for 4 years before founding Qloo in 2012.
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