Senior Machine Learning Scientist

Summary

Join Qloo's team as an ML Scientist and play a crucial role in developing and implementing cutting-edge machine learning models. You will collaborate with cross-functional teams on diverse projects, from data exploration and model development to deployment and monitoring. Responsibilities include model development and deployment, data analysis and optimization, pipeline development, collaboration, model performance monitoring, experimentation, knowledge sharing, and continuous learning. This high-impact role requires 3+ years of experience in machine learning or ML engineering, a relevant degree (advanced degree preferred), proficiency in Python and PySpark, and excellent communication skills. Qloo offers a competitive salary, excellent health insurance, 401k matching, paid time off, parental leave, company holidays, professional development opportunities, and a supportive work environment.

Requirements

• 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
• 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

Responsibilities

• Develop, test, deploy, and maintain machine learning models and algorithms, ensuring their scalability, robustness, and performance in production
• Conduct data preprocessing, feature engineering, and exploratory analysis to optimize AI/ML models
• Design, build, and enhance efficient machine learning pipelines, ensuring their scalability and performance
• Work closely with software engineers, data engineers, and other teams to integrate ML models into production systems, aligning with business requirements
• Implement tools for real-time model monitoring, evaluate performance, and drive continuous improvements to models and pipelines
• Explore emerging ML techniques, deep learning methods, and advanced algorithms to enhance model capabilities and introduce new solutions
• 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
• Stay current with industry trends and emerging technologies in data science and machine learning to identify new opportunities and techniques

Preferred Qualifications

An advanced degree is highly preferred

Benefits

• 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
• $140,000 - $180,000 a year