Vision
Robust Intelligence's mission is to eliminate AI Risk. As we transition into a world that is adopting AI into automated decision processes, we inherit a great deal of risk. Data drift, misclassified data, prediction biases and adversarial input easily distort AI outputs and can have detrimental effects. In addition, with viral adoption of new Generative AI based APIs, new risk vectors like prompt injection, prompt extraction, PII exfiltration, factual inconsistency and hallucinations pose significant threat to organizations. Our flagship products are built to be integrated with existing AI systems and protect against real-time API based 3rd-party AI access to eliminate these risks.
Robust Intelligence is a leading provider of end-to-end AI security solutions for enterprises. Our cutting-edge technology automates the testing and validation of AI models, safeguarding organizations from security, ethical, and operational risks. Backed by prominent investors including Sequoia Capital and Tiger Global, we are proud to work with an expanding list of customers, including JPMorgan Chase, Expedia, ADP, IBM, Deloitte, and key players in the public sector such as the U.S. Intelligence Community and the Department of Defense.
Advancing the state of AI is a collaborative process that requires unusually varied skills and perspectives. To that end, we have built a multidisciplinary team with increasingly diverse backgrounds. Together, we're building the future of secure, trustworthy AI.
About the Role
Robust Intelligence is the leader in AI Security.
As a Data Platform Engineer you will be a part of the our ML Data and Quality team and help the team build the platform for data generation used for model development, off-line experiment pipelines, data collection and labeling mechanism, and data management. You will help shape the processes surrounding data creation, storage, and usage. You are at home working with a cross-functional team of researchers, engineers, and security experts to design, develop and deploy innovative AI solutions.
As an Data Engineer you will
- Be primarily responsible for building the ML data infrastructure based on the requirements of the ML team and the product needs, including data lineage, provenance, and validation.
- Be hands-on and build data workflows, data experimentation pipelines and ML evaluation strategies.
- Collaborate with ML and research to understand data needs, help build novel data generation algorithms, and help build and enforce processes around data creation and usage.
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You'll have the opportunity to contribute to our overall machine learning and data management culture as a member of the team.
What we look for:
- A BS or MS in Computer Science/Engineering.
- An attitude of hands-on learning and constant experimentation to decompose and understand problem areas.
- Experience with MLOps frameworks like MLFlow, model hosting services like HuggingFace or Baseten is a big plus
- Experience with some backend datastore similar to SnowFlake or DataBricks.
- Strong programming skills in generic programming languages such as Python or Golang.
- Excellent written and verbal communication skills, strong analytical and problem-solving skills.
Technologies we use:
- Python and specifically numpy, pandas
- Bonus: ML frameworks like pytorch, tensorflow, fastai, xgboost, catboost, lightgbm, sklearn etc
- Bonus: Golang
