Job Overview
At Dynamo AI, we are seeking a Senior Software Engineer to join our team in San Francisco. This role is pivotal in designing, developing, and maintaining robust, secure, and scalable infrastructure and applications. You will play a crucial role in deploying our advanced machine learning models in diverse production environments, ensuring optimal performance and reliability.
Responsibilities
- Design and develop systems on our Kubernetes-based infrastructure, ensuring seamless deployment and management of our ML models.
- Maintain and enhance the infrastructure and applications, focusing on scalability, security, and high availability.
- Implement industry best practices in software development and infrastructure management to achieve excellence in operations and service delivery.
- Take complete ownership of the infrastructure and applications, proactively identifying and addressing issues to ensure our products consistently meet the highest standards of quality and performance in customer environments.
- Implement and maintain automated testing and CI/CD pipelines to ensure code quality and deployment efficiency.
Qualifications
- 3+ years of experience developing and managing scalable services in Kubernetes.
- Proficiency in Kubernetes, cloud services, and modern DevOps practices.
- Strong coding skills in one or more programming languages.
- Excellent problem-solving abilities and a commitment to innovation and continuous improvement.
- Experience in deploying machine learning models in production is a plus.
Dynamo AI is committed to maintaining compliance with all applicable local and state laws regarding job listings and salary transparency. This includes adhering to specific regulations that mandate the disclosure of salary ranges in job postings or upon request during the hiring process. We strive to ensure our practices promote fairness, equity, and transparency for all candidates.
Salary for this position may vary based on several factors, including the candidate's experience, expertise, and the geographic location of the role. Compensation is determined to ensure competitiveness and equity, reflecting the cost of living in different regions and the specific skills and qualifications of the candidate.
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