Software Engineer, Backend/Applied ML (Safety & Integrity)Active$150K–$300K

We’re looking for a talented and creative Software Engineer to join our Safety Engineering team at Character. AI !

What you'll do

• Architect & Build: Design, develop, and maintain highly scalable, resilient, and performant backend systems that power our integrity and safety features.

• Lead Complex Solutions: Lead the technical design and implementation of sophisticated backend solutions for detecting, preventing, and mitigating a wide array of integrity risks. This includes traditional issues (e.g., content classification, spam, etc.) as well as emerging threats related to Generative AI (e.g., misuse of generative models, generation of harmful or biased content, etc).

• Apply Machine Learning: Conceptualize, develop, deploy, and iterate on machine learning models and algorithms to address complex integrity challenges. This includes areas like content classification (including AI-generated content), anomaly detection, risk scoring, behavior analysis, and developing safeguards for Generative AI systems (e.g., robust content filtering, bias mitigation techniques, and output monitoring).

• Cross-Functional Collaboration: Work closely with product managers, data scientists, AI researchers, security teams, and operations to define requirements, design innovative solutions, and deliver impactful integrity systems, especially for Generative AI products.

• Technical Strategy & Roadmap: Drive the long-term technical vision and roadmap for backend integrity systems and applied ML capabilities, with a keen eye on addressing Generative AI safety concerns with an alignment with company objectives.

• Mentorship & Leadership: Provide technical guidance and mentorship to other engineers on the team and across the organization, fostering a culture of engineering excellence.

What they're looking for

• + years of professional software engineering experience, with a strong: emphasis on backend systems development.
• Bachelor's, Master's, or PhD degree in Computer Science, Engineering, or a related technical field.
• Proven track record of designing, building, and operating complex,: large-scale, and highly available distributed systems.
• Expertise in one or more backend programming languages such as Python, Go, Java, or C++.
• Hands-on experience in applying machine learning techniques to solve: real-world problems, specifically with demonstrable experience in addressing integrity, trust, or safety challenges.
• Solid understanding of the machine learning lifecycle, including data: gathering and cleaning, feature engineering, model selection, training, validation, A/B testing, deployment, and operational monitoring.
• Exceptional problem-solving abilities, with a knack for tackling ambiguous: and technically challenging problems.
• Proven ability to work in a fast-paced development environment and deliver timely results.