
Senior Machine Learning Expert
18 hours ago
- Develop a deep understanding of different types of data, metrics, and KPIs to identify and formulate data science problems that drive impactful solutions.
- Lead the development of cutting-edge machine learning and data science solutions, including large language models, computer vision models, and advanced ad & content targeting.
- Review and develop mathematical solutions to complex data science problems, ensuring technical excellence and scalability.
- Utilize Agentic AI, Gen AI, and LLM-based models to formulate and identify business use cases, providing advanced insights and opportunities to move the business needle.
- Define and implement best practices for the team, setting high standards for technical quality and innovation.
- Create and deliver compelling presentations to senior leadership and business stakeholders, effectively communicating business insights and recommendations.
- Manage and oversee data science projects, ensuring timely delivery and alignment with business objectives.
- Leverage industry best practices and tools to continually improve the team's ability to build and deploy machine learning models.
- Work closely with platform, content, user data, and product partners to expand and enhance data science capabilities.
- Drive observability, scalability, cost-optimization, and performance tuning for data science models and services.
- Motivate, inspire, and create a culture of experimentation and data-driven innovation, advocating for customer-centric solutions.
- Collaborate with principal engineers to productionalize models and create a robust architecture for deploying machine learning solutions at scale.
- 12-14 years of experience in data science and machine learning algorithms, with at least 3 years of leading and managing a software development team.
- Strong understanding of modern ML approaches (e.g., GBDT, CNN, LSTM, GRU, HRNN, transformer models, variational auto-encoders).
- Experience with Classical ML Techniques, Deep Learning, NLP, LLMs, Causal Inference, and proficiency in ML tools and frameworks (Keras, PyTorch, scikit-learn, Spark).
- Proficiency in programming languages such as Python or R.
- Experience with implementing and managing MLOps frameworks to enhance reproducibility, scalability, and maintainability of machine learning models.
- Familiarity with real-world ML systems, including configuration, data collection, data verification, feature extraction, resource and process management, analytics, training, serving, validation, experimentation, and monitoring.
- Experience with offline experimentation and A/B testing.
- Good understanding of operating machine learning solutions at scale, covering the end-to-end ML workflow.
- Understanding of batch and streaming data processing techniques.
- Experience of Databricks, AWS, GCP, or Azure.
- Experience with Docker and Kubernetes.
- Experience with CI/CD tools like GitHub Actions, Jenkins, etc.
- Familiarity with agile practices and processes.
- Excellent written and verbal communication skills, with the ability to contribute to technical documentation and provide on-call support.
- BA/BS in Data science, machine learning, statistics, mathematics, economics, industrial engineering, or other quantitative discipline is required. Masters/PhD is a plus.
- A competitive salary and benefits package.
- The opportunity to work with a talented and diverse team of professionals.
- Access to ongoing training and development opportunities.
- A dynamic and supportive work environment.
- The chance to make a meaningful contribution to the success of our organization.
- Championing Inclusion: We strive to create an inclusive and welcoming workplace where everyone feels valued and respected.
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