Cognizant is looking to solve business-critical problems such as fraud detection, predictive maintenance, and search optimization using machine learning and deep learning
Requirements
- Strong foundation in statistics, linear algebra, calculus, and probability.
- Proven experience in supervised and unsupervised learning, regression, classification, and deep learning.
- Proficiency in Python and R for data analysis, modeling, and visualization.
- Experience with scalable ML systems (e.g., MapReduce, streaming architectures).
- Hands-on experience with Azure OpenAI, ML Ops, and cloud-based ML platforms.
- Familiarity with NLP, computer vision, and image processing using OpenCV.
- Knowledge of SEO and data-driven optimization techniques is a plus.
Responsibilities
- Design, develop, and deploy machine learning models for business-critical applications such as fraud detection, predictive maintenance, and search optimization.
- Conduct hypothesis-driven research, build and test multiple models, and refine them for performance and accuracy.
- Perform exploratory data analysis (EDA) to uncover insights and inform model development.
- Utilize Azure OpenAI Service, Cloud AutoML, and ML Ops practices for scalable and efficient model deployment.
- Build and manage data pipelines using Airflow and other orchestration tools.
- Apply deep learning techniques using PyTorch and TensorFlow for NLP, computer vision, and time-series analysis.
- Leverage OpenCV for image processing and computer vision tasks.
Other
- MS or PhD in Computer Science, Statistics, Electrical Engineering, or a related field.
- Excellent communication skills and ability to work independently and in teams.
- Please note, this role is not able to offer visa transfer or sponsorship now or in the future
- Travel requirements not mentioned
- Preferred: Experience with JavaScript/Java, time-series modeling, and a portfolio of projects (GitHub, publications, etc.).
- Ability to work in Redwood City, CA
