Data Platform Engineer

Robust Intelligence's mission is to eliminate AI Risk. As the world increasingly adopts AI into automated decision processes, we inherit great risk. 

Our flagship product is built to be integrated with existing AI systems to enumerate and eliminate risks caused by unintentional and intentional (adversarial) failure modes. With Generative AI becoming increasingly popular, new vulnerabilities and attacks present a significant threat to AI companies and their consumers. Our Generative AI Firewall provides a safety net against these failure modes.

At Robust Intelligence, we have built a multidisciplinary team of ML Engineers, AI security experts, and software engineers to advance the state of AI security. Together, we're building the future of secure, trustworthy AI.

About The Role

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.
• 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.
• 4+ years of industry experience
• 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