Staff Data Engineer- AQNav
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
As a Data Engineer on the AQNav Team, you will play a crucial role in bridging the gaps between data acquisition and processing, model research, and real-time operation, ensuring the seamless development and operation of machine learning models. Your primary focus will be on designing, building, and maintaining scalable, automated data and machine learning pipelines that facilitate the development, deployment, and monitoring of models in applied research environments. You will collaborate closely with ML researchers and engineers, software engineers, and a diverse team of scientists to streamline the end-to-end data pipeline and machine learning lifecycle.
What You’ll Do
- Build data ingestion, storage, processing, and reporting pipelines in the cloud
- Build out data storage, management, reporting tools, and dashboards
- Build infrastructure for comparing, tracking, and reporting new model performance against existing data sets
- Build infrastructure to track the history of model versions and performance
- Establish alerts/notifications when models deviate from expected behavior
- Iterate rapidly with the prototyping team, domain experts, and external partners to develop insights and continue product development
- Investigate and develop rigorous, cutting-edge solutions to challenging structured and unstructured calibration problems for real-time application.
- Solve algorithmic challenges to construct an automated, verifiable, and scalable calibration system
- Automate the data processing and ML training/reporting pipelines
About You
- 7+ years of experience designing and creating data processing solutions
- Proficiency with tools and programming languages related to data engineering (Hadoop, Spark, Scala, Python, etc.)
- Experience in developing pipelines in Cloud environments such as GCP, AWS, or Azure and willing to utilize GCP
- Proficiency with databases and SQL language
- Ability to work in a tight-knit team environment, ability to communicate effectively with others, and able to take initiative and run with minimal supervision
- Excited to learn new technologies and skills
- BS, MS, or PhD in a relevant degree (Data Science, Computer Science, Electrical Engineering, Mechanical Engineering, or other related field)
- Eligible to work on Federal Contracts with the US Government
Nice to Haves
- Experience with data architecture design
- Experience with MLOps
- Experience with Databricks, Snowflake, Redshift, Vertica, Greenplum, or other similar engines
- Passionate about physics
- Knowledgeable about navigation
- Experience with sensor prototypes
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.
SandboxAQ welcomes all.
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