Character.AI01/07/2026
Software Engineer, Backend/Applied ML (Safety & Integrity)
Salary not specified
MARKET
15,900 ₽median for this role
Data Scientist · 115 jobs with disclosed pay
5,000half of the offers: 12,796–20,50043,793
The employer didn't disclose pay — compare with the market yourself.
Полная занятостьУдалёнка
Responsibilities
- 01Design, develop, and maintain highly scalable, resilient, and performant backend systems that power integrity and safety features
- 02Lead the technical design and implementation of sophisticated backend solutions for detecting, preventing, and mitigating a wide array of integrity risks
- 03Conceptualize, develop, deploy, and iterate on machine learning models and algorithms to address complex integrity challenges
- 04Work closely with product managers, data scientists, AI researchers, security teams, and operations to define requirements and deliver impactful integrity systems
- 05Drive the long-term technical vision and roadmap for backend integrity systems and applied ML capabilities
- 06Provide technical guidance and mentorship to other engineers on the team and across the organization
- 07Advocate for and implement best practices in software engineering, distributed systems design, data engineering, and the full lifecycle of ML model development
- 08Continuously analyze and improve the performance, scalability, reliability, and cost-effectiveness of existing integrity platforms and ML models
- 09Keep abreast of emerging threats, new technologies, and advancements in backend engineering, distributed systems, and the application of machine learning to trust and safety
Requirements
- 018+ years of professional software engineering experience, with a strong emphasis on backend systems development
- 02Bachelor's, Master's, or PhD degree in Computer Science, Engineering, or a related technical field
- 03Proven track record of designing, building, and operating complex, large-scale, and highly available distributed systems
- 04Expertise in one or more backend programming languages such as Python, Go, Java, or C++
- 05Hands-on experience in applying machine learning techniques to solve real-world problems, specifically with demonstrable experience in addressing integrity, trust, or safety challenges
- 06Solid understanding of the machine learning lifecycle, including data gathering and cleaning, feature engineering, model selection, training, validation, A/B testing, deployment, and operational monitoring
- 07Exceptional problem-solving abilities, with a knack for tackling ambiguous and technically challenging problems
- 08Proven ability to work in a fast-paced development environment and deliver timely results
- 09Strong communication, interpersonal, and leadership skills, with the ability to articulate complex technical concepts to diverse audiences
- 10You care deeply about Trust & Safety and see it as a value-add to the business
- 11Prior experience in a dedicated Trust & Safety, Integrity, or Risk engineering team
- 12Contributions to open-source projects or publications in relevant fields
- 13Experience leading large, cross-cutting technical projects