Education Requirements:

• BS in CS or Engineering

Experience Requirements:

• 5 years using BI / Analytics solutions

• 4 years in RDBMS and big data tech like Hadoop

• 3 years in Java and Advanced Analytics like Scala/SPSS

• Previous work in industrial IOT and manufacturing

Benefits:

• Diverse medical, dental and vision options

• 401k matching program

• Unlimited paid time off

• Parental leave and flexibility for all parents and caregivers

• Support of country-specific visa needs for international employees living in the Bay Area

Responsibilities:

• Designing, developing, and maintaining backend services and tools to support our ML inference pipelines, data tools, and security systems.

• Collaborating with teams across the organization to integrate backend solutions seamlessly with our front-end and ML components.

• Ensuring high levels of scalability, reliability, and security in the systems you build.

• Participating in code reviews, testing, and documentation efforts to maintain our high-quality software standards.

• Continuously learning about ML workflows and contributing innovative ideas to further enhance our AI platform.

Responsibilities:

• Designing, building, and maintaining state-of-the-art data tools that convert raw data into high-quality datasets for ML training and labeling.

• Developing robust workflows and pipelines for data transformation, filtering, analysis, and cleaning that enhance dataset quality.

• Collaborating with ML researchers, data scientists, and engineers to ensure our data tools meet the rigorous standards required for enterprise-grade AI.

• Continuously evaluating and integrating emerging technologies to keep our data curation processes at the forefront of innovation.

• Driving the evolution of our data platform to support scalable, efficient, and effective data annotation and labeling pipelines.

Responsibilities:

• Building small, specialized models to conduct detailed safety evaluations of LLM outputs.

• Developing classifiers to detect unsafe, biased, or harmful responses, and integrating them into our response modeling pipelines.

• Collaborating with fine-tuning and training teams to ensure that safety protocols are embedded within our model development lifecycle.

• Conducting in-depth research on adversarial attacks, model vulnerabilities, and safety enhancements to stay ahead of emerging threats.

• Serving as a key technical leader, driving the innovation and evolution of our LLM safety practices, ensuring our models operate reliably and securely in enterprise settings

Responsibilities:

• Designing, developing, and maintaining secure backend systems that underpin our AI platform.

• Implementing security features and best practices throughout our codebase to safeguard data and infrastructure.

• Collaborating with cross-functional teams to integrate security considerations into all aspects of product development and deployment.

• Conducting regular security reviews, audits, and code assessments to proactively identify and mitigate vulnerabilities.

• Building and maintaining secure CI/CD pipelines with integrated security scanning and vulnerability management tools.