Role Description: Senior Machine Learning Engineer
Role Purpose:
Wasabi is seeking an experienced Senior Software Engineer with a solid background in machine learning and software development to contribute to Wasabi AiR. In the spirit of our disruptive approach to cloud storage our AI/ML product, Wasabi AiR resets the paradigm of how cloud storage and machine-learning compliment each other and enrich the accessibility of data. This role is perfect for candidates who thrive in team-oriented environments, enjoy mentoring, lead complex projects, and are passionate about building scalable, high-quality machine learning solutions.
*Principals only. No recruiters.
Responsibilities:
- Drive advancements in AI, keeping up-to-date with the latest research and applying innovative techniques in production.
- Develop and refine computer vision algorithms for tasks such as object detection, tracking, and scene understanding, with a focus on designing and implementing NLP models and algorithms.
- Apply machine learning technologies to enable systems to learn and adapt to complex situations.
- Collaborate closely with cross-functional teams to ensure smooth integration of machine learning capabilities across projects.
- Perform testing, debugging, and documentation of machine learning models to ensure reliable installation and maintenance.
Requirements:
- 8+ years in architecting, designing, developing, integrating, and supporting complex AI systems.
- Proficiency in one or more object-oriented programming languages, such as Python, Java, or Golang, with experience in distributed systems.
- Deep understanding of large-scale data processing systems and computing frameworks, with a proven ability to optimize and troubleshoot machine learning models.
- Hands-on experience ML training and fine-tuning large models with in-house data.
- Strong communication and problem-solving abilities, with the ability to document and adhere to timelines effectively.
- Masters Degree or PhD in Computer Science, Data Science, or a related field preferred.
