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Senior Machine Learning Scientist
Qloo IT Solutions
posted 1mon ago
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Flexible timing
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Job Description
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.
Youll 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.
Employment Type: Full Time, Permanent
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Flexible timing
Alternate Saturday off
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