You'll immediately provide value by:
- 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.
To be a successful match you must have:
- 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 we offer:
- Potential equity package
- Excellent health insurance coverage, with ability to join group dental and vision for a nominal fee
- 4% 401K matching
- 20 paid time off days
- 5 paid sick days
- 12 weeks of paid parental leave
- 10+ annual company holidays
- Opportunities for professional development and growth within a dynamic environment
- A supportive and inclusive company ethos where your ideas are valued, your contributions are recognized, and your impact is tangible
- The chance to be part of a small but mighty team that's making waves in the industry and shaping the future of technology
- Beautiful HQ in Soho, NYC with the opportunity to work in-office, if desired
Top Skills
What We Do
Qloo – the cultural AI.
Qloo has developed cutting-edge machine learning processes and AI algorithms to predict taste for any target audience and map relationships within and between cultural domains, including: Music, Film, TV, Dining, Nightlife, Fashion, Books, Travel and Tech.
Qloo has mapped more than a quarter-trillion cultural correlations, and makes this intelligence readily available to individuals, developers, and leading brands. Qloo's cultural AI is currently powering personalization and informing key decisions for market leaders in tech, financial services, entertainment, automotive, fashion, CPG and hospitality.
Qloo is headquartered and lovingly built in NYC.
Gallery
