As a Hindi Transcriber/Annotator, you will be responsible for creating time-aligned, verbatim transcriptions with correct punctuation and capitalization. You will also be familiar with subtitling technical requirements and can specify correct, exact time segments for speakers speaking in an overlapping manner. Additionally, you will have familiarity with various annotation requirements and can create annotations/tags following detailed instructions with minimal training.

Responsibilities:

• Create time-aligned, verbatim transcriptions with correct punctuation and capitalization
• Familiarity with subtitling technical requirements and can specify correct, exact time segments for speakers speaking in an overlapping manner
• Familiarity with various annotation requirements and can create annotations/tags following detailed instructions with minimal training

Requirements:

• Native fluency in Hindi with an impeccable grasp of grammar, spelling, and punctuation
• Experience with subtitling software (e.g., Subtitle Edit, Aegisub, EZTitles, or CaptionHub, etc.)
• Strong attention to detail, with an ability to spot a single misplaced comma or a 0.5-second timing drift
• Deep understanding of the target language culture, idioms, and social context to ensure the transcription is done by meaning base

Benefits:

• Competitive pay
• Work on popular broadcast events across TV, streaming, games, and much more
• Early access to unreleased content
• Flexible project volume
• Set your own schedule
• Constructive feedback and support

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This team moves very quickly. Claude writes a lot of the code we commit, which means the bottleneck isn't typing , it's judgment, taste, and the ability to react to what researchers need next. You'll iterate on data collection strategies to distill the knowledge of thousands of human experts around the world into our models, and you'll do it in a loop that closes in hours and days, not quarters or months.

Our work spans teaching models to use computers effectively, advancing code generation through RL, pioneering fundamental RL research for large language models, and building the scalable training methodologies behind our frontier production models. The RL org is organized around four goals: solving the science of long-horizon tasks and continual learning, scaling RL data and environments to be comprehensive and diverse, automating software engineering end-to-end, and training the frontier production model.

Our engineering teams build the environments, evaluation systems, data pipelines, and tooling that make all of this possible , from realistic agentic training environments and scalable code data generation to human data collection platforms and production training operations.

Responsibilities:

• Build and extend web platforms for RL environment creation, management, and quality review , including environment configuration, versioning, and validation workflows
• Develop vendor-facing interfaces and tooling that let external partners create, submit, and iterate on training environments with minimal friction
• Design and implement platforms for human data collection at scale, including labeling workflows, quality assurance systems, and feedback mechanisms that surface reward signal integrity issues early
• Build evaluation dashboards and observability UIs that give researchers real-time insight into environment quality, training run health, and reward hacking
• Create backend services and APIs that connect environment authoring tools, data collection systems, and RL training infrastructure
• Build and expand scalable code data generation pipelines, producing diverse programming tasks with robust reward signals across languages and difficulty levels
• Develop onboarding automation and documentation tooling so new vendors and internal users ramp up in hours, not weeks
• Partner closely with RL researchers, data operations, and vendor management to translate ambiguous requirements into well-scoped, well-designed products

You May Be a Good Fit If You:

• Have strong software engineering fundamentals and real full-stack range , you're comfortable owning a surface from database schema to frontend
• Are proficient in Python and a modern web stack (React, TypeScript, or similar)
• Have a track record of shipping systems that solved a hard problem, not just shipped on time , e.g. you built the thing that made your team 10x faster, or the internal tool nobody thought was possible
• Operate with high agency: you identify what needs to be done and drive it forward without waiting for a ticket
• Have found yourself wondering "why isn't this moving faster?" in previous roles , and then have done something about it
• Care about UX and can build interfaces that are intuitive for both technical researchers and non-technical labelers
• Communicate clearly with researchers, operations teams, and engineers, and can turn vague asks into well-scoped work
• Thrive in a fast-moving environment where priorities shift, Claude is your pair programmer, and the next problem is often one nobody has solved before
• Care about Anthropic's mission to build safe, beneficial AI and want your work to contribute directly to it

Strong Candidates May Also Have:

• Built data collection, labeling, or annotation platforms , ideally ones that had to scale across many vendors or many task types
• Background building multi-tenant platforms with role-based access, audit trails, and vendor management workflows
• Experience with cloud infrastructure (GCP or AWS), Docker, and CI/CD pipelines
• Familiarity with LLM training, fine-tuning, or evaluation workflows
• Experience with async Python (Trio, asyncio) or high-throughput API design
• Background in dashboards, monitoring, or observability tooling
• Experience working directly with external vendors or partners on technical integrations
• A background that isn't a straight line , e.g. math or physics into SWE, competitive programming, research into engineering, or a side project that outgrew its scope

Representative Projects:

• Building a unified platform for human data collection that integrates labeling workflows, vendor management, and QA for complex agentic tasks
• Developing vendor onboarding automation that handles Docker registry access, API token management, and environment validation
• Creating evaluation and observability dashboards that catch reward hacks, measure environment difficulty, and give real-time feedback during production training
• Building environment quality review workflows that let researchers browse, grade, and provide feedback on training environments
• Developing automated environment quality pipelines that validate correctness and difficulty calibration before environments hit production training
• Building internal tools for browsing and analyzing training run results, environment statistics, and data collection progress

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Key Responsibilities:

• Work on various client projects to train generative AI models by creating prompts and responses based on instructions provided and established best practices for quality prompts.
• Generate similar prompts and responses based on given examples.
• Use communication channels such as Slack, Teams, and SharePoint to learn about new projects, collaborate with your team, and ask questions.
• Learn new software programs on the job.
• Provide supporting documentation when the AI fails.

Requirements:

• Experience: 0-2 years
• Excellent communication skills (oral and written)
• Qualification: Bachelor's degree (any stream)
• Preferred: Good understanding of AI
• Ability to gain new skills and knowledge through hands-on experience
• Keen eye for detail
• Demonstrated ability to work independently
• Strong time management skills
• Exemplify the quality of doing 'get it done' attitude, including a high level of accountability, transparency, and teamwork first & foremost

Benefits:

• Medical Insurance
• Term Insurance
• Accidental Insurance
• Lunch/Dinner provided at subsidized rates

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At OpenAI, our Trust, Safety & Risk Operations teams safeguard our products, users, and the company from abuse, fraud, scams, regulatory non-compliance, and other emerging risks. We operate at the intersection of operations, compliance, user trust, and safety working closely with Legal, Policy, Engineering, Product, Go-To-Market, and external partners to ensure our platforms are safe, compliant, and trusted by a diverse, global user base.

The Global Safety Response Operations team provides 24/7 coverage for user safety, risk, and regulatory escalations across OpenAI’s products, handling the highest-priority cases that require human judgment and rapid response. The team operates as the core escalation and delivery arm of OpenAI’s safety operations, ensuring that our products remain safe and aligned with policy while enabling timely, empathetic, and consistent user support.

About the Role

The Global Safety Response Operations Lead is a hands-on team lead who both manages a regional Safety Response team and personally handles high-risk safety cases. This role combines frontline safety work with people leadership, operational ownership, and cross-functional coordination.

You will lead a team of Safety Response Analysts who handle OpenAI’s most sensitive and high-impact cases, while also personally contributing to casework for complex, high-risk, or high-visibility issues. You will own the execution of high severity escalations in your region and ensure proper execution and communication to cross functional stakeholders

You will be accountable for ensuring your region consistently meets utilization, quality, and SLA targets while serving as the operational interface with Product, Policy, Legal, Investigations, and regional stakeholders.

This is a 24/7 global operation that requires flexibility to support rotating shifts, including nights, weekends, and holidays, as part of a leadership on-call model.

In This Role, You Will:

• Lead and coach a regional team of Safety Response Analysts, ensuring high performance, engagement, and consistent decision quality.

• Own regional operational outcomes, including utilization, SLA adherence, backlog health, and quality benchmarks.

• Handle and oversee the most complex and high-risk cases, serving as the first line of escalation and incident lead for your region.

• Contribute directly to frontline work (20–30%), including investigations, enforcement decisions, and regulatory or legal escalations.

• Partner cross-functionally with Product, Policy, Legal, Investigations, and local market teams to execute safety outcomes and manage risk.

• Drive operational excellence and continuous improvement, improving workflows, tools, automation, and escalation paths.

• Identify emerging risks and trends, translating frontline insights into actionable recommendations for policy, product, or enforcement.

You Might Thrive in This Role If You:

• You have 5+ years in Trust & Safety, Risk Operations, Investigations, Fraud, Annotation, or platform integrity.

• You have 4+ years of people leadership or senior-level operational ownership.

• You are a strong decision-maker in ambiguous, high-risk environments, able to balance speed, accuracy, and defensibility when handling sensitive or high-impact cases.

• You communicate complex safety and risk decisions clearly and credibly, whether writing escalation narratives, briefing Legal or Policy, or aligning Product and leadership during incidents.

• You can translate between frontline operations and strategic stakeholders, turning messy real-world cases into structured insights and turning policy or product direction into clear, executable guidance for your team.

• You are skilled at influencing without authority, building trust with Product, Policy, Legal, Investigations, and regional partners to drive alignment and resolve ambiguity.

• You are deeply familiar with content moderation, user safety, fraud, or developer risk frameworks, including the legal, policy, and technical considerations that shape enforcement.

• You use data, tooling, and automation to improve quality, efficiency, and scale to not just measure performance, but to make better decisions.

• You are comfortable leading in a 24/7, high-pressure operational environment, providing calm, credible leadership during incidents, spikes, and regulatory or reputational events.

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.

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