Senior Machine Learning Engineer skilled in developing sophisticated predictive models and algorithms. The candidate should have proficiency in Python and R, along with experience in using machine learning libraries like Scikit-learn, TensorFlow, and Keras. Expertise in statistical modeling, data mining, and natural language processing is desirable. Familiarity with cloud platforms like AWS or Azure for deploying ML models is a plus.
Project Details:
Develop and refine machine learning models for predictive analytics, working in tandem with data scientists and product teams.
Engage in the entire ML lifecycle, from data preprocessing to model deployment, ensuring scalability and efficiency in cloud environments.
Document methodologies and results, and participate in the design of system architecture for machine learning applications.
Job Experience:
Machine Learning, Data Mining
Python, R
Scikit-learn, TensorFlow, Keras
NLP techniques
Cloud platforms (AWS, Azure)
Master's or PhD in a relevant field
Oxford is an Equal Employment Opportunity Employer. All qualified applications will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Oxford will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law. Oxford provides supplemental medical (we do not offer major medical), dental, vision, life, and disability benefit plans along with a 401(k) Retirement Savings Plan. Paid holidays based on eligibility and paid sick leave for applicable jurisdiction, as required. Oxford is committed to working with and providing reasonable accommodation to individuals with physical and mental disabilities. If you need special assistance or an accommodation while seeking employment, please email oxfordbenefitsgroup@oxfordcorp.com. We will make a determination on your request for reasonable accommodation on a case-by-case basis.
