Senior Machine Learning Scientist

Summary

Join GoDaddy's DnAI team as a Senior Machine Learning Scientist and contribute to cutting-edge machine learning models for Pricing + Bundling and Generative AI projects. You will develop and implement advanced algorithms, design and refine models, analyze data, and collaborate with cross-functional teams. This remote position requires 4+ years of experience in machine learning engineering, proficiency in Python, and strong knowledge of machine learning algorithms. You will work with the AWS ecosystem and contribute to standardized processes for model evaluation and deployment. GoDaddy offers a range of benefits, including paid time off, retirement savings, bonuses, health benefits, and parental leave.

Requirements

• 4+ years of overall experience and 2+ years of experience in machine learning engineering or related roles
• Proficient in Python programming language
• Strong knowledge of machine learning algorithms, tools, and techniques, such as supervised and unsupervised learning, deep learning, computer vision, natural language processing, etc
• Experience in building ML models in production using AWS ecosystem, especially ML related services such as SageMaker
• Ability to work independently and collaboratively with cross-functional teams
• Excellent communication and presentation skills
• Experience in writing unit tests and documentation for ML code
• Familiarity with software engineering best practices, such as version control, code review, CI/CD, etc

Responsibilities

• Develop and implement advanced machine learning algorithms for Pricing and Generative AI projects using PyTorch
• Design and refine ML models to enhance their performance, scalability, and robustness
• Analyze and interpret complex data sets to inform model development and ensure accuracy and effectiveness
• Stay abreast of the latest developments in machine learning and artificial intelligence, integrating new methodologies and techniques as appropriate
• Collaborate with cross-functional teams to integrate ML solutions within broader product and platform initiatives
• Contribute to the development of standardized processes for model evaluation, validation, and deployment to production environments
• Drive the exploration and adoption of cutting-edge ML technologies to maintain our competitive edge in the industry

Preferred Qualifications

• Experience in working with large-scale and complex data sets
• Master’s degree or PhD in computer science, engineering, statistics, or related fields
• Experience in applying machine learning to domains such as e-commerce, finance, health care, etc
• Experience in using ML tools such as Mlflow for model lifecycle management
• Experience with common ML libraries and frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn
• Familiarity with prompt engineering and large language models (LLM) is a plus
• Proficiency in multiple programming languages
• Understanding of containerization technologies like Docker and orchestration tools like Airflow

Benefits

• Paid time off
• Retirement savings (e.g., 401k, pension schemes)
• Bonus/incentive eligibility
• Equity grants
• Participation in our employee stock purchase plan
• Competitive health benefits
• Other family-friendly benefits including parental leave