The Company You’ll Join
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 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.
Read more about our recent Series C funding here.
The team you’ll work with:
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. If you're a proactive problem-solver with a passion for machine learning, we'd love to meet you.
Hear what the team has to say – “...the fantastic team I work with creates an environment where we encourage each other and collaborate, which naturally leads to creative ideas. The complex technical challenges we face not only keep things interesting but also push us to find unique solutions, and AI constantly inspires me to excel in my role.” - Elizabeth, VP of Applied ML.
The impact you’ll have:
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.
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
