ZipRecruiter

Log In

1

Manager Ai Translator Jobs (NOW HIRING)

Domino Data Lab

Staff Product Manager, AI Factory

... management, onboarding, inventory, and audit-ready documentation. * Lead the next generation of AI ... You operate as a peer in system design conversations, not a translator. * Customer-first instincts.

Propio

AI Engineer II - Translation

Leawood, KS · On-site

Work closely with linguists, product managers, and engineers to integrate AI into translation pipelines and gather domain feedback. * Continuously evaluate and benchmark model performance using ...

SaidGig

Mandarin Translator for AI Model Training

$45 - $95/hr

... AI required. Key Responsibilities * Provide accurate and nuanced translation and interpretation ... Ability to work independently and manage priorities in a remote environment. * Excellent ...

New

next page

Showing results 1-20

All JobsAi Translator JobsManager Ai Translator Jobs

Manager Ai Translator information

See salary details

$12

$25

$40

How much do manager ai translator jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for manager ai translator in the United States is $25.65, according to ZipRecruiter salary data. Most workers in this role earn between $21.15 and $27.88 per hour, depending on experience, location, and employer.

What is a Manager AI Translator?

A Manager AI Translator is a professional who oversees the integration and management of AI-powered translation tools within an organization. They are responsible for ensuring that machine translation systems function effectively, meet quality standards, and align with business goals. Their role often includes coordinating between technical teams, linguists, and stakeholders to optimize translation workflows and address any issues that arise. Additionally, they may analyze translation data, implement process improvements, and stay updated on advances in AI translation technology.

How does a Manager AI Translator typically collaborate with cross-functional teams to ensure accurate and contextually relevant translations?

A Manager AI Translator frequently works alongside software engineers, linguists, and product managers to oversee the integration of AI translation tools and ensure linguistic accuracy. They coordinate regular meetings to review translation outputs, discuss context-specific challenges, and address feedback from quality assurance teams. This collaborative approach helps identify nuances, cultural references, and technical jargon that may not be captured by automated systems, ensuring the final translation meets both technical and user expectations.

What are the key skills and qualifications needed to thrive as a Manager AI Translator, and why are they important?

To thrive as a Manager AI Translator, you need a strong background in linguistics, natural language processing (NLP), and team leadership, usually supported by a relevant degree and experience in translation technologies. Familiarity with AI translation tools such as Google Translate API, DeepL, CAT tools, and data annotation platforms is typically required, along with knowledge of project management systems. Exceptional communication, problem-solving, and cross-cultural sensitivity are vital soft skills for coordinating teams and ensuring translation accuracy. These abilities are crucial for delivering high-quality multilingual content and leading teams in a rapidly evolving technological landscape.

What is the difference between Manager Ai Translator vs Data Scientist?

AspectManager Ai TranslatorData Scientist
Required CredentialsBachelor's degree in AI, linguistics, or related field; experience in translation and AI toolsBachelor's or master's in data science, statistics, or computer science; programming skills
Work EnvironmentCollaborative teams, AI development projects, translation platformsData analysis, modeling, coding, research environments
Industry UsageTech companies, AI translation services, multinational corporationsTech, finance, healthcare, research institutions

The Manager Ai Translator focuses on overseeing AI-driven translation projects, combining linguistic expertise with AI tools. In contrast, a Data Scientist analyzes data to develop models and insights. Both roles require technical skills, but their core functions and industry applications differ significantly.

What cities are hiring for Manager Ai Translator jobs? Cities with the most Manager Ai Translator job openings:
What are the most commonly searched types of Ai Translator jobs? The most popular types of Ai Translator jobs are:
What states have the most Manager Ai Translator jobs? States with the most job openings for Manager Ai Translator jobs include:
Manager Ai Translator jobs near you

Technical Account Manager - AI Infrastructure

Prime Intellect

San Francisco, CA • On-site

Full-time

Re-posted 25 days ago

Job description

Technical Account Manager
Own Your Intelligence
Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.
Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators - including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.
Your Role
Prime Intellect serves some of the most sophisticated AI teams in the world that depend on our compute and infrastructure to train and deploy production AI systems. The Customer Success Manager is the person who makes sure those customers succeed, scale, and keep building with us.
This is not a traditional Customer Success role. Our customers run large-scale training jobs, scale inference workloads against real production traffic, and depend on cluster reliability and performance the way most companies depend on their cloud provider. The work spans the technical and the commercial - you'll be reading Grafana dashboards and discussing cluster performance with a customer's ML infrastructure team in the morning, and partnering with Sales on a capacity expansion in the afternoon.
You'll own a portfolio of enterprise customers end-to-end and build the relationships that make Prime Intellect the partner of choice for their AI infrastructure.
Responsibilities
Customer Ownership
  • Own a portfolio of enterprise customers end-to-end - adoption, retention, expansion, and overall health
  • Build deep relationships with technical and executive stakeholders at each customer, from ML engineers to engineering leadership
  • Drive customer outcomes: faster time-to-value on first workloads, smooth scaling as their usage grows, and meaningful expansion as their AI ambitions expand

Technical Partnership
  • Understand each customer's training and inference workloads at a real technical level - what models they're training, what infrastructure they need, what their performance bottlenecks are
  • Partner with customers' engineering teams on cluster performance, capacity planning, workload optimization, and migration
  • Translate customer needs into clear, prioritized feedback for our Engineering and Product teams

Expansion & Renewals
  • Identify expansion opportunities ahead of the customer - anticipate scaling needs, surface new use cases, drive adoption of new products (Lab, Inference, additional compute capacity)
  • Partner with Sales on renewal conversations and growth motions
  • Maintain visibility into the economics of each customer relationship, in partnership with Finance and Compute

Operational Excellence
  • Serve as the first line for customer-facing operational issues - usage questions, capacity changes, SLA tracking, incident communications
  • Build the cross-functional connective tissue between Sales, Engineering, Finance, and customers

What We're Looking For
  • 3-6 years in Customer Success, Technical Account Management, Solutions Engineering, or adjacent roles at infrastructure, cloud, or AI/ML companies
  • Strong technical fluency - comfortable reading dashboards, discussing infrastructure architecture, and engaging with customer engineering teams without a translator
  • Strong commercial instincts - you understand that Customer Success is a revenue function, not a support function, and you can drive real expansion alongside technical outcomes
  • Deep customer empathy combined with high judgment - you advocate for customers internally while making the calls that are right for the business
  • Excellent verbal and written communication, especially when explaining complex technical issues to non-technical stakeholders and vice versa
  • High ownership - you see gaps and build the fix before anyone asks
  • Comfortable in ambiguity and speed; this market doesn't slow down
  • AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster

Bonus:
  • Direct experience at a cloud provider, AI infrastructure company, or compute marketplace
  • Familiarity with GPU economics, training and inference workloads, or compute consumption patterns
  • Background as a TAM or Solutions Architect at a hyperscaler (AWS, GCP, Azure) or specialized cloud provider
  • Working knowledge of usage-based pricing, capacity commitments, and consumption-based contracts
  • You've been an early Customer Success hire at a high-growth company

What We Offer
  • Cash Compensation Range of $160,000 - $200,000 + meaningful equity
  • Flexible work (remote or San Francisco)
  • Visa sponsorship and relocation support
  • Professional development budget
  • Team off-sites and conferences
  • A front-row seat to building the infrastructure layer for open AI

Apply