AI Product Engineer
Varsity Tutors, a Nerdy Company · Dallas, TX · 3 wk ago
RemoteRemoteEngineeringFull-time
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About the role
The Senior Software Engineer (AI-Native) position is for individuals with extensive experience in developing software solutions that leverage artificial intelligence technologies. The Staff Engineer (AI-Native) role is for experienced professionals looking to take on more responsibility and leadership roles.
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Responsibilities
- Design, develop, and maintain high-quality software applications using AI-native technologies.
- Collaborate with cross-functional teams including product managers, data scientists, and other engineers to deliver innovative AI-driven solutions.
- Contribute to the continuous improvement of existing systems and processes.
- Stay updated with the latest advancements in AI and machine learning.
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Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Minimum 5 years of relevant work experience in software engineering or a related field.
- Experience with AI and machine learning frameworks such as TensorFlow, PyTorch, or similar.
- Strong problem-solving skills and ability to work independently and as part of a team.
- Excellent communication and collaboration skills.
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Qualifications
- Proven track record of delivering high-quality software products.
- Experience with cloud platforms like AWS, Azure, or Google Cloud.
- Knowledge of database management systems such as MySQL, PostgreSQL, or MongoDB.
- Experience with version control systems like Git.
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Skills
- Proficiency in programming languages such as Python, Java, or C++.
- Understanding of software development methodologies and best practices.
- Ability to analyze complex problems and design effective solutions.
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Benefits
- Competitive compensation package.
- Flexible working hours and remote work options.
- Professional development opportunities.
- Health insurance and retirement benefits.
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Pay
Compensation is commensurate with experience and qualifications.
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Schedule
Hours are flexible and can be arranged based on the candidate's availability.