ML Scientist

Employment Type: Full Time

Position Overview

Qloo is seeking a highly motivated and skilled ML Scientist to join our growing team. At Qloo, we leverage cutting-edge Taste AI™ technology to analyze vast amounts of data and uncover deep insights into consumer preferences, helping brands connect with their ideal customers. We are committed to privacy, using only anonymized cultural and behavioral data. Following our Series C funding, we are expanding our reach and redefining what's possible with Taste AI. This role is instrumental in driving our next stage of growth.

About Qloo

At Qloo, we build AI solutions that power personalization for leading companies. We foster a culture of curiosity, encouraging our team to tackle tough challenges and push boundaries. We value autonomy, ownership, and collaboration, believing that diverse perspectives lead to better solutions. We support our team through professional growth opportunities, a flexible and inclusive environment, and regular team activities.

"The team culture at Qloo is highly collaborative and supportive, with a strong emphasis on mutual assistance. Each team member is approachable and committed to lending a hand, creating an environment where everyone feels supported and valued." – Sreekant, VP of API Engineering

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.

Responsibilities

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.