At G-P, our mission is to break down barriers to global business, enabling opportunities for everyone, everywhere. With remote-first and diverse teams all around the world, our people are key to achieving this mission. That’s why we trust our Dream Team members with the flexibility and autonomy to do their best and most innovative work, encourage and support their personal growth and career development, and believe in recognition for a job well done.

Our industry-leading SaaS-based Global Employment Platform™ enables our customers to expand and grow into 180 countries, creating more opportunities for global success – without requiring entity or subsidiary setup. The technical opportunities you’ll experience here have a positive impact on people and their work/life possibilities around the world. Beyond the power of our platform, we never forget that behind every hire is a human being. And that brings us to you. 

If you have a passion for AI and MlOps, are a deep innovator, and want to solve complex problems that lead to a world of positive results, consider G-P. Here, your knowledge and experience will be crucial to helping design and develop high-performing cloud-based software products using traditional Agile methodologies and modern frameworks.

Beyond a competitive compensation and benefits package, what we offer to all employees along the way is the clear and simple promise of Opportunity Made Possible. Come expand your skills in new ways and experience the thrill of your best innovations becoming reality.

Key Responsibilities:

• Lead the design and implementation of complex AI solutions using cloud computing technologies, with a strong focus on MLOps practices to streamline and automate machine learning lifecycle management.
• Oversee collaborations with data scientists and AI researchers to ensure efficient deployment and scalability of machine learning models and AI applications within cloud environments.
• Architect and manage cloud resources and infrastructure, emphasizing cost efficiency, security, compliance, and MLOps best practices.
• Develop and refine automation scripts and CI/CD pipelines to support MLOps strategies, ensuring seamless and rapid deployment, monitoring, and maintenance of AI systems.
• Monitor the performance of AI applications, ensuring high availability, efficient resource utilization, and proactive scalability and maintenance.
• Evaluate and integrate the latest trends and tools in AI, machine learning, cloud technologies, and MLOps, advocating for and implementing innovative solutions that enhance our capabilities.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, with at least 5 years of relevant experience in cloud engineering and AI deployment.
• Spent at least 5 years as a software engineer
• Deep expertise in AWS, both serverless and otherwise.
• Experience architecting AWS solutions for optimal performance and pricing.
• Experience with Terraform
• Advanced proficiency in programming in Python.
• Extensive experience with Docker other containerization and orchestration technologies.
• Proven track record in designing and implementing effective MLOps architecture to support AI and machine learning model lifecycle management at scale.
• Solid knowledge of networking, security, and database management in cloud environments.
• Leadership skills with the ability to mentor a team, solve complex problems, and deliver results in a dynamic and collaborative environment.

Preferred Qualifications:

• Advanced certifications in cloud technologies and MLOps-specific certifications 
• Experience with Kubernetes Controllers
• Have a good working knowledge of Deep Neural Networks, and other machine learning algorithms with a strong grasp on data pipelining and data drift.

The annual gross base salary range for this position is $178,400 to $200,000. Actual compensation for this position may vary and will depend on multiple factors including relevant qualifications, experience, education and geographic location. This position is also eligible for an annual bonus dependent on various factors, including and without limitation, individual and company performance in addition to base salary.

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