# Software Engineer, Implicit Signals
**Company:** [OpenAI](https://scaleengineer.com/companies/openai)
Join OpenAI's Implicit Signals team to build classification and evaluation systems that power research and post-training capabilities. This role combines software engineering expertise with data engineering to develop scalable services, online/offline pipelines, and tools that help researchers assess model behavior and iterate rapidly. You'll own production systems from architecture through deployment while partnering closely with machine learning engineers and data scientists to deliver reliable, high-performance evaluation infrastructure.
**Role:** Backend Engineer
**Seniority:** Senior
**Locations:** San Francisco
**Salary:** 347000–445000 USD
[Apply](https://jobs.ashbyhq.com/openai/c7bcdaec-9714-44b0-8ba8-adc824594b54)
Canonical: https://scaleengineer.com/jobs/openai/software-engineer-implicit-signals
---
## Responsibilities

- Design and Build Software Services: Architect and develop scalable software services and RESTful APIs for configuring, running, and managing classifiers and evaluations. Focus on clean API design patterns, request validation, error handling, and comprehensive API documentation to support diverse user workflows and integration requirements.
- Build and Operate Classification Pipelines: Develop and maintain robust online and offline classification pipelines that execute reliably and efficiently at scale. Implement data processing workflows, manage batch and real-time data processing, implement fault tolerance mechanisms, and ensure systems remain operational under production workloads.
- Optimize Model Serving Performance: Improve inference infrastructure performance across throughput, latency, concurrency, and compute utilization metrics. Implement caching strategies, optimize serialization and deserialization, profile bottlenecks, leverage GPU acceleration, and implement performance monitoring to maintain SLAs.
- Create Developer Tools and Experimentation Platform: Build intuitive tools and interfaces that simplify experimentation, debugging, and rapid iteration for researchers and data scientists. Develop logging and visualization capabilities, create experiment tracking systems, implement debugging utilities, and reduce time-to-insight for model evaluation workflows.
- Own Production Reliability and Observability: Take ownership of production system reliability, implement comprehensive observability solutions, and lead incident response efforts. Design monitoring and alerting systems, implement distributed tracing, establish runbooks, reduce operational burden through automation, and drive continuous improvement in system stability.
- Collaborate with Machine Learning Engineers: Partner with ML engineers to integrate new classification capabilities and models into production systems. Assist with model packaging, containerization, versioning strategies, and deployment processes while ensuring production systems maintain performance and reliability standards.
- Engage with Post-Training Researchers: Work closely with post-training researchers and data scientists to understand their workflows, pain points, and requirements. Identify high-impact product improvements, shape platform roadmap based on user feedback, and deliver features that accelerate research velocity and model evaluation cycles.

## Requirements

### education

- {"name":"Computer Science or Related Field","description":"Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience. Strong foundation in algorithms, data structures, system design, and software engineering principles."}

### technical

- {"name":"Distributed Systems Design","description":"Proven experience designing, building, and operating distributed systems and microservices architectures at scale. Understanding of scalability patterns, eventual consistency, data consistency models, and system design tradeoffs in production environments."}
- {"name":"API Design and Development","description":"Strong fundamentals in RESTful API design, gRPC, versioning strategies, and request/response handling. Experience with authentication, rate limiting, pagination, error handling, and creating developer-friendly APIs that scale."}
- {"name":"Concurrency and Performance Engineering","description":"Deep understanding of concurrent programming patterns, thread management, async/await patterns, and performance optimization. Experience with profiling tools, identifying bottlenecks, implementing caching strategies, and optimizing for throughput and latency."}
- {"name":"Production Systems and Observability","description":"Experience operating production systems at scale with comprehensive monitoring, logging, and alerting. Ability to investigate complex production issues, implement distributed tracing, design observability strategies, and manage incident response."}
- {"name":"Complex Problem Solving","description":"Ability to investigate complex production problems systematically, understand failure modes, make sound architectural tradeoffs between performance, reliability, and operational complexity, and communicate decisions clearly."}
- {"name":"End-to-End Software Ownership","description":"Track record of owning software projects from initial design and architecture through implementation, testing, deployment, and ongoing operation. Experience making critical decisions at all stages of the software lifecycle."}

### experience

- {"name":"Backend and Systems Engineering","description":"5+ years of professional backend software engineering experience building and operating production systems. Demonstrated ability to design scalable architectures and handle high-traffic, mission-critical services."}
- {"name":"Production Operations and Incident Management","description":"Hands-on experience operating production systems, responding to incidents, and improving system reliability. Track record of reducing operational burden through automation and proactive monitoring."}
- {"name":"Data Engineering and Pipelines","description":"Experience building data processing pipelines, ETL workflows, or data infrastructure. Understanding of data consistency, batch vs. real-time processing, and data quality assurance."}
- {"name":"Cross-functional Collaboration","description":"Experience working directly with technical users, researchers, or product teams to understand requirements and prioritize work. Strong communication skills and ability to translate complex technical problems into actionable solutions."}

## Skills

### required

- {"name":"Python or Go","description":"Expert-level proficiency in Python for data-heavy applications and rapid prototyping, or Go for high-performance systems and concurrency. Comfortable with performance profiling, debugging, and optimization in your primary language."}
- {"name":"Distributed Systems Architecture","description":"Strong understanding of distributed system patterns including service orientation, eventual consistency, message queues, and asynchronous processing. Experience with design tradeoffs and failure scenarios."}
- {"name":"Database Design and Optimization","description":"Proficiency with both SQL and NoSQL databases. Experience with query optimization, indexing strategies, schema design, and understanding of when to use different database paradigms."}
- {"name":"System Design and Scalability","description":"Demonstrated ability to design systems that scale horizontally, handle high throughput, optimize latency, and maintain reliability under production load. Experience with load balancing, caching, and resource optimization."}
- {"name":"API and Service Design","description":"Experience designing and implementing robust APIs with proper error handling, versioning, documentation, and consideration for developer experience at scale."}
- {"name":"Monitoring and Observability","description":"Hands-on experience implementing comprehensive monitoring, logging, alerting, and distributed tracing. Ability to design observability solutions that enable rapid incident investigation and resolution."}

### preferred

- {"name":"Model Serving and ML Systems","description":"Experience with model serving platforms, ML inference optimization, or ML platform engineering. Understanding of containerization, model versioning, and deployment strategies for machine learning systems."}
- {"name":"Data Engineering and Pipelines","description":"Experience building robust data pipelines, ETL systems, batch processing workflows, or stream processing systems. Familiarity with Apache Spark, Kafka, Airflow, or similar distributed data tools."}
- {"name":"Kubernetes and Container Orchestration","description":"Experience deploying and managing containerized services on Kubernetes or similar orchestration platforms. Understanding of resource management, service mesh, and cloud-native deployment patterns."}
- {"name":"AI and Machine Learning Concepts","description":"Working knowledge of machine learning concepts, statistical methods, and model evaluation. Familiarity with LLMs, transformers, and modern deep learning approaches. Understanding of how ML systems work end-to-end."}
- {"name":"Performance Optimization","description":"Track record of optimizing complex systems for throughput, latency, and resource efficiency. Experience with profiling tools, identifying bottlenecks, and implementing performance improvements in production systems."}
- {"name":"Product Thinking","description":"Strong product judgment and ability to partner with technical users to understand needs, prioritize features, and shape product direction. Experience with user-focused product development."}

## Tech stack

### tools

- {"name":"Docker","description":"Container technology for packaging services, ensuring reproducibility, and streamlining deployment across environments."}
- {"name":"Kubernetes","description":"Container orchestration platform for managing, scaling, and operating services in production at scale."}
- {"name":"Git and Version Control","description":"Essential for collaborative software development, code review, and maintaining codebase history."}
- {"name":"CI/CD Platforms","description":"Automation tools like GitHub Actions, GitLab CI, or similar for automated testing, building, and deployment pipelines."}
- {"name":"Prometheus and Grafana","description":"Monitoring and observability stack for metrics collection, alerting, and visualization of system performance."}
- {"name":"ELK Stack or DataDog","description":"Logging and centralized log analysis platforms for troubleshooting production issues and understanding system behavior."}
- {"name":"Jira and Confluence","description":"Project management and documentation tools common in enterprise software development environments."}

### others

- {"name":"Message Queues","description":"Technologies like Apache Kafka, RabbitMQ, or AWS SQS for asynchronous processing, event streaming, and decoupling services."}
- {"name":"Cloud Platforms","description":"Experience with AWS, Google Cloud Platform, or Azure for infrastructure, managed services, and cloud-native deployment."}
- {"name":"Distributed Tracing","description":"Tools like Jaeger, Zipkin, or vendor solutions for tracing requests through distributed systems and identifying performance bottlenecks."}
- {"name":"Load Testing and Performance Analysis","description":"Tools for benchmarking, stress testing, and profiling applications to identify performance limitations and optimize systems."}
- {"name":"AI Agents and LLM Tools","description":"Familiarity with AI agent frameworks and large language model APIs for accelerating development velocity and cross-functional work."}

### databases

- {"name":"PostgreSQL","description":"Robust relational database commonly used for structured data, state management, and ACID-compliant transactions in production systems."}
- {"name":"Redis","description":"In-memory cache and data store for high-performance data access, caching, and real-time data processing applications."}
- {"name":"DynamoDB or MongoDB","description":"NoSQL solutions for document storage, flexible schemas, and horizontal scalability in distributed systems."}
- {"name":"BigQuery or Data Warehouses","description":"Large-scale data warehousing and analytics platforms for batch processing classification results and evaluation metrics."}

### languages

- {"name":"Python","description":"Primary language for data processing, service development, and rapid prototyping. Used extensively in machine learning and data engineering workflows at AI research organizations."}
- {"name":"Go","description":"High-performance systems language for building concurrent services, distributed systems, and performance-critical infrastructure components."}
- {"name":"TypeScript or JavaScript","description":"For frontend tooling, APIs, and cross-platform development where rapid iteration is valued."}
- {"name":"SQL","description":"Essential for data querying, analytics, and relational database interactions in evaluation and classification systems."}

### frameworks

- {"name":"FastAPI","description":"Modern Python framework for building high-performance APIs with automatic validation, async support, and comprehensive documentation generation."}
- {"name":"Django or Flask","description":"Established Python web frameworks for building scalable backend services and REST APIs."}
- {"name":"gRPC","description":"High-performance RPC framework for efficient service-to-service communication in distributed systems."}
- {"name":"TensorFlow Serving or Ray Serve","description":"Model serving frameworks commonly used in ML infrastructure for deploying and managing inference workloads at scale."}

## Benefits

### benefits

## Compensation

- **max:** 0
- **min:** 0
- **currency:** 
- **stockOptions:** false

## Interview process

### steps

- {"name":"Initial Screening Call","description":"Introductory conversation with a recruiter to discuss your background, career goals, and alignment with the role. Share specific examples of complex systems you've built or operated at scale."}
- {"name":"Technical Phone Screen","description":"Conversation with a senior engineer covering system design principles, your approach to complex architectural problems, and experience with distributed systems. Be prepared to discuss tradeoffs, scalability considerations, and failure recovery strategies."}
- {"name":"System Design Interview","description":"Deep-dive system design session where you'll architect solutions for large-scale infrastructure challenges similar to the role. Demonstrate your ability to design scalable APIs, optimize performance, and consider reliability at the design stage."}
- {"name":"Coding and Implementation Interview","description":"Technical assessment of your coding ability, typically involving building a service component, optimizing code for performance, or solving problems requiring strong systems thinking and implementation quality."}
- {"name":"Product and Collaboration Interview","description":"Conversation with team members who use the platform to discuss your approach to product thinking, user collaboration, and understanding technical requirements. Share examples of how you've partnered with non-engineer users to drive impact."}
- {"name":"ML Systems and Production Operations Interview","description":"Discussion of your experience with machine learning infrastructure, model serving, and operating complex production systems. Share examples of incident response, reliability improvements, and scaling challenges you've overcome."}
- {"name":"Leadership and Culture Fit Discussion","description":"Final conversation with engineering leadership about your working style, how you approach ambiguous problems, ownership mentality, and fit with OpenAI's mission-driven culture and AI-forward engineering practices."}

## Full description
**About the Team**

Our team builds classification and evaluation systems that give post-training and research teams fast, reliable feedback on model behavior. We combine machine learning and production engineering to make these capabilities accurate, efficient, and useful at scale, helping researchers assess changes and improve models and products.

We work closely with researchers and data scientists and have broad ownership of the software that makes these capabilities available. Our work spans real-time systems, data engineering, model serving, and tools for experimentation, with careful attention to performance, reliability, and privacy.

**About the Role**

We’re looking for a software engineer to build and evolve our classification and evaluation platform. You’ll develop services, online and offline pipelines, and tools that help researchers and data scientists turn an idea into a working measurement and iterate on it quickly.

This role combines software and data engineering with hands-on production ownership. You’ll shape the architecture, deliver new capabilities, improve inference efficiency, and keep the system dependable as workloads and requirements evolve. Strong candidates will bring deep software engineering expertise and an interest in building a technical product in close partnership with its users.

**In this role, you will:**

* Design and build software services and APIs for configuring, running, and managing classifiers and evaluations.
* Build and operate online and offline classification pipelines that support reliable, efficient execution at scale.
* Improve model-serving performance, including throughput, latency, concurrency, and compute utilization.
* Build tools that make experimentation, debugging, and iteration straightforward for researchers and data scientists.
* Own production reliability, observability, and incident response, and reduce the operational burden of running the platform.
* Partner with machine learning engineers to bring new classification capabilities into production.
* Work closely with post-training researchers and data scientists to understand their workflows, identify high-impact improvements, and shape the product.

**You might thrive in this role if you have:**

* Experience designing, building, and operating software services or distributed systems at scale.
* Strong fundamentals in API design, concurrency, caching, performance, and failure recovery.
* Ability to investigate complex production problems and make sound architectural tradeoffs.
* A track record of owning software from initial design through deployment and ongoing operation.
* Strong product judgment and an interest in working directly with technical users.
* Comfort with ambiguous problems and broad ownership across multiple parts of a system.
* Fluency in using AI agents to move quickly across multiple workstreams in a fast-paced environment.
* Interest in machine learning, data science, and statistics; experience with model serving, ML platforms, or inference optimization is a plus.

**About OpenAI**

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. 

For additional information, please see [OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement](https://cdn.openai.com/policies/eeo-policy-statement.pdf).

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through [this form](https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA). No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this [link](https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241).

[OpenAI Global Applicant Privacy Policy](https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf)

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.