Staff Machine Learning Operations Engineer - AQMed
Ready to join the AQ era?
SandboxAQ is solving challenging problems with AI + Quantum for positive impact. We partner with global leaders in government, academia, and the private sector to identify applications that would benefit from quantum-based applications to current and future commercial challenges. We engage with customers early and throughout the development process to improve market fit.
Our team’s unique approach enables cross-pollination across a diverse range of fields, from physics, computer science, neuroscience, mathematics, cryptography, natural sciences and more! Our success comes from coalescing diverse talent to create an environment where experimental thinking and collaboration yield breakthrough AI + Quantum solutions. Join a culture where thought leadership, diverse talent, employee engagement, and technological impact will create the next tech uproar.
We are deeply committed to education as a means to advance quantum solutions and computing initiatives. We invest in future talent through internship programs, research papers, developer tools, textbooks, educational talks/events and partnerships with universities/talent hubs to attract multi-disciplinary talent. Our hope is to inspire people from all walks of life to be prepared for the quantum era and encourage a path in STEM.
About the Role:
Sandbox AQ operates at the intersection of AI/ML and quantum, and you will provide the AI/ML and computational infrastructure backbone to enable a new generation of health technologies. This includes the strategic architecting of data, computing, and ML infrastructure from prototype to production, as well as working with the research and product engineering teams to ensure that Sandbox SaaS products are always pushing the state of the art. You will bring MLOps expertise to bear in making important architectural design decisions to ensure the resultant pipelines are scalable, robust, fault-tolerant, secure, and maintainable. With your experience, you will provide guidance for AI/ML research scientists in following best practices around software engineering in order to facilitate production level code and an easier path to deployment.
What You’ll Do:
Technical Leadership
-
- Make clear, well-researched, and experience-based architectural recommendations, which support the delivery of complex AI SAAS products to customers.
- Analyze and communicate the critical trade-offs in competing architectural options, by articulating the impact on the product quality and scalability, technical complexity, timeline for delivery, and ongoing maintenance requirements.
- Guide the AI/DS team toward continual improvement in fundamental engineering best practices.
Technical Implementation
-
- Build complex yet robust MLOps pipelines to support the delivery of AI SAAS products.
- Provide experienced recommendations for the best AWS services to utilize for optimal MLOps pipeline delivery.
- Implement systems to train existing Dl and ML models at scale, and iterate rapidly toward new AI/ML products.
- Implement tools and methodologies that support solid data governance, including monitoring of traceability, data quality, data security, etcetera.
- Conduct code reviews for more junior AI/ML scientists
About You:
- You understand Deep Learning and Machine Learning well enough to help deploy, maintain, and monitor models in production environments.
- You have 7+ years of experience in AWS, MLOps, and AI/ML, which allows you to make skillful recommendations about which services would be best to use for a given AI Product.
- You thrive in a startup environment and are able to balance the need for speed with the desire to build solid, reliable software.
You know how to listen and communicate respectfully with key stakeholders to understand their requirements and collaboratively work through any mutual concerns, before finalizing an architectural decision.
- You are a “doer” with communication skills; you know how to ask the right questions and how to talk to the key stakeholders, but once the product goals are clear, you implement rapidly and skillfully.
- You love to learn about the latest evolutions in AI/ML, and you get a deep intrinsic reward from finally deploying these cutting-edge AI/ML models and monitoring their impact.
The US base salary range for this full-time position is expected to be $188k - $309k per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.