DUST Identity provides security, integrity, and traceability to the world’s supply chains. DUST, or Diamond Unclonable Security Tag, uses diamond particles as unique and unclonable markers on individual items. Think of a barcode, but invisible, unfalsifiable, and made with diamonds! With DUST, customers can ensure that every physical object — whether an airplane part, microprocessor, or priceless work of art — is verified, authenticated, and ultimately, trusted.
DUST Identity is a fast-growing venture-backed startup at the intersection of innovations in materials, hardware, and software. DUST Identity is looking for new team members who are eager to take on the challenge of building the industry standard for physical object identification and security.
DUST Identity is seeking a talented, experienced Data Engineer to help shape our Data science team. In this role, you will provide infrastructure and tools that enable our machine learning and computer vision teams to build, train, and monitor algorithm development. In addition, you will ingest image-based data from multiple sources, including our cutting-edge hardware systems, to help build and train algorithms. Finally, you will manage and assist in data analysis, while formalizing, documenting, and refining our learnings.
Responsibilities include but are not limited to:
- Architect and build our data warehouse: You will design and implement a data warehouse and necessary data pipelines to help streamline our machine learning algorithm development efforts. You will build scalable infrastructure that will enable our team to build models, test hypotheses, and draw conclusions efficiently, keeping information security at the forefront.
- Scale our machine learning efforts: You will build data and processing infrastructure to enable our ML engineers to deploy existing models to our pipelines and expand their analytics efforts.
- Collaborate with the hardware, software, and R&D teams while adapting to rapidly evolving requirements from existing customers and new markets.
- Manage and prioritize projects and maintain accountability to tight timelines.
- Build and improve our data extraction framework: You will design and improve upon our current system for ingesting and integrating data from disparate sources.
- Automate and scale: You will develop systems and tools to configure, monitor, and orchestrate our data infrastructure, as well as perform intelligent data scrubbing.
- Develop data standards: You will help develop our internal standards for data management and data governance using standard data modeling techniques and per the needs of our R&D and Operations teams.
What You Bring
- Bachelor’s degree in Statistics, Data Science, Applied Mathematics, Computer Science, Engineering, Physics, or a related field.
- 3-5 years experience designing, building, and maintaining data platforms.
- Experience with core AWS services and concepts (S3, IAM, autoscaling groups) or DevOps experience.
- Experience designing and deploying tools in an existing development ecosystem.
- Experience working with database design and management, especially with relational (SQL), document-based and semi-structured (NoSQL) data, as well as key-value stores.
- Familiarity with Infrastructure as Code (e.g. AWS CDK, Terraform, etc.).
- Experience writing data-intensive services in Python, Scala or Julia, etc.
- Experience tuning stream and batch processing applications to increase throughput.
- Computer/machine vision or biometric technology experience.
- Experience with machine learning platforms/frameworks such as Tensorflow or PyTorch.
- Experience with Kafka and/or Apache Spark.
- Experience with data visualization platforms.
- Use and experience with AWS ML products, such as Rekognition, SageMaker, etc.
Details You Should Know
- Start Date: Immediately
- Must have legal right to work in the United States without sponsorship.
- Location: Princeton, NJ
- Compensation: Market Competitive + Equity
- Travel: None
- DUST Identity is an equal opportunity employer.
What We Offer
- Award-winning startup with a product that matters
- An abundance of snacks/coffee
- Medical, dental, vision, LTD, and life insurance
- Flexible paid time off policy
- Casual dress