Designing and operating cloud - based MLOps capabilities supporting analytical and generative AI models. Collaborating with data science and business teams for high - impact AI solutions.
About the role
- Develop and validate machine learning models at PayPal for innovative AI/ML solutions. Collaborate with data scientists and software engineers to enhance services and customer experiences.
Responsibilities
- Develop and optimize machine learning models for various applications.
- Preprocess and analyze large datasets to extract meaningful insights.
- Deploy ML solutions into production environments using appropriate tools and frameworks.
- Collaborate with cross-functional teams to integrate ML models into products and services.
- Monitor and evaluate the performance of deployed models.
Requirements
- 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
- Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
- Several years of experience in designing, implementing, and deploying machine learning models.
- Advanced knowledge of statistical and machine learning models (e.g., logistic regression, time series analysis, random forests, SVMs, XGBoost, CNNs/RNNs)
- Possessing advanced coding skills in dealing with big data (e.g., Scikit-learn in Python, Tensorflow, Hadoop, Spark, SQL, etc.)
- Relevant Modeling experience in credit scoring, fraud detection, financial forecasting, or marketing analytics obtained either in academic or financial industry.
- Ability to work effectively both independently and in a team environment.
- Ability to communicate effectively and establish constructive relationship with stakeholders.
Benefits
- Generous paid time off
- Healthcare coverage for you and your family
- Resources to create financial security
- Support for your mental health
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Machine Learning Engineer analyzing data structures and developing ML models for customer profiling in Azerbaijan. Collaborating on probabilistic modeling and data quality improvement.
Machine Learning Engineer at HackerRank working on integrity systems to improve model quality. Collaborating on strategies for new signals like audio analysis and behavioral anomalies.
Machine Learning Engineer developing integrity systems for assessing model quality at HackerRank. Collaborating on multimodal signal processing and improving model performance.
Architect designing enterprise - grade AI/ML architectures for Quantiphi. Leading AI applications and ML strategy with a focus on scalability, security, and integration.
Software Engineer for ML Infrastructure at Slack, architecting systems to support large scale AI deployment and reliability. Engage in deep systems engineering focusing on ML lifecycle and infrastructure scalability.
Machine Learning Engineer at Winnow developing AI solutions for food waste reduction. Collaborate with cross - functional teams and leverage cutting - edge technologies in food recognition.
Senior Engineer developing AI/ML solutions to enhance patient care at Edwards Lifesciences. Collaborating with cross - functional teams to deliver impactful technologies in healthcare.
Machine Learning Engineer designing and deploying machine learning models for DXC Technology. Collaborating with data scientists and optimizing solutions for impactful results.
Senior Machine Learning Engineer at APS leading MLOps initiatives and collaborating across teams. Designing and implementing scalable machine learning solutions with a focus on real - time decision - making.