Machine Learning Engineer
hace 7 días
Key responsibilities include:
Designing and implementing machine learning workflows and infrastructure to productize AI models and sustain them in production.
Responsibilities include preparing data for ML models at scale, building interfaces for ML model consumption, enabling ML Ops for continuous delivery and automation of ML pipelines, and building AI productization platforms.
Strong analytical skills are required, including the ability to scope out business problems, identify and access relevant data, make appropriate assumptions, perform insightful analysis, and draw conclusions relevant to the business problem.
Ability to present information professionally and concisely with supporting data.
Qualifications:
Minimum Qualifications:
1+ years of experience or knowledge in classical machine learning algorithms, ML algorithm evaluation, building/interaction with AI/ML models, and using Python and SQL.
Preferred Qualifications:
Strong knowledge of advanced data structures, experience using Github, Cloud Foundry, Kubernetes, and other cloud deployment platforms, OO programming in Python, Python package creation and management, API design experience, and experience working with mathematical optimization algorithms.
Inside Intel:
Enable amazing computing experiences with Intel Software, shaping the way people think about computing across CPU, GPU, and FPGA architectures. Get hands-on with new technology and collaborate with the smartest people in the business.
Posting Statement:
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Benefits:
We offer a total compensation package that ranks among the best in the industry, including competitive pay, stock, bonuses, and benefit programs.
Working Model:
This role will be eligible for our hybrid work model, allowing employees to split their time between working on-site and off-site.
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