Project Manager, Applied AI

ABOUT the company

AI is changing how the world communicates — and the company is leading that transformation.

We're on a mission to make the world's information accessible to everyone, regardless of the language they speak. We use cutting-edge AI, machine translation, and human-in-the-loop expertise to translate content faster, more accurately, and more cost-effectively without compromising on brand, voice, or quality.

At the company, we empower our teammates with leading tools, global collaboration, and growth opportunities to do their best work. Our company virtues—Work together, win together; Find a way or make one; Dance in the customer's shoes; Quicker than they expect; Quality is Job 1—guide everything we do. We are trusted by Intel Corporation [link for members] Canva [link for members] the United States Department of Defense [link for members] the United States Air Force [link for members] ASICS [link for members] and hundreds of global Enterprises. Backed by Sequoia, Intel Capital, and Redpoint, we’re building a category-defining company in a $50B+ global translation market being redefined by AI.

We are looking for a data-driven Project Managers to lead our large-scale multilingual data collection and Large Language Model (LLM) evaluation initiatives. In this role, you will be the operational backbone of our AI development, orchestrating global teams of annotators and data specialists.

If you thrive in a fast-paced environment where you can optimize workflows for productivity, quality, and throughput, we want to hear from you

KEY RESPONSIBILITIES

• PROJECT MANAGEMENT

• End-to-End Delivery: Manage the full lifecycle of AI data projects, from scoping and guidelines creation to data delivery and post-mortem analysis.

• Pipeline Management: Oversee large-scale data pipelines for multilingual data collection (audio, text, image) and LLM evaluation (RLHF, SFT, ranking, and safety testing).

• QUALITY ASSURANCE & PERFORMANCE MONITORING

• KPI Tracking: rigorously monitor and report on key performance indicators, including:

• Throughput: Volume of data processed per hour/day.

• Quality: Accuracy scores, Inter-Annotator Agreement (IAA), and gold-set performance.

• Productivity: Cost-per-task and worker efficiency rates.

• Quality Control: Run QA loops, root-cause analysis for quality dips, and corrective training for annotator pools.

• Dashboards: Maintain dashboards to visualize project health and flag bottlenecks in real-time.

• STAKEHOLDER MANAGEMENT

• Global Coordination: Manage relationships with data experts and crowd pools, ensuring adherence to SLAs regarding localized nuances and linguistic accuracy.

• Cross-Functional Collaboration: Liaise with Applied AI Technical Ops teams. Translate technical requirements into clear, actionable guidelines for non-technical annotators.

• Feedback Loops: Facilitate continuous feedback loops where data insights drive updates to annotation guidelines and model fine-tuning strategies.

QUALIFICATIONS

ESSENTIAL SKILLS & EXPERIENCE

• Experience: 3-5+ years of project management experience, specifically within AI/ML data operations.

• LLM Knowledge: Strong understanding of LLM training processes (Pre-training, SFT, RLHF) and evaluation methodologies (Human-in-the-loop, red teaming).

• Data Proficiency: Advanced proficiency in Excel/Google Sheets; ability to write SQL queries to extract and analyze performance data.

• Methodology: Proven track record using Agile, Scrum, or Kanban methodologies to manage complex workflows.

• Communication: Exceptional ability to write clear, unambiguous guidelines for multilingual audiences.

PREFERRED QUALIFICATIONS (NICE TO HAVES)

• Multilingual: Fluency in a second language is highly desirable.

• Technical Tools: Experience with data annotation platforms (e.g. Scale AI, Super Annotate) and project management tools (e.g. Jira).

• Education: Background in ML Engineering, Computer Science, Data Science and Project Management training.

OUR STORY

Our founders, Spence and John met at Google working on Google Translate. As researchers at Stanford and Berkeley, they both worked on language technology to make information accessible to everyone. While together at Google, they were amazed to learn that Google Translate wasn’t used for enterprise products and services inside the company.The quality just wasn’t there. So they set out to build something better. The company was born.

The company has been a machine learning company since its founding in 2015. At the time, machine translation didn’t meet the quality standard for enterprise translations, so the company assembled a cutting-edge research team tasked with closing that gap. While meeting customer demand for translation services, the company has prioritized investments in Large Language Models, human-in-the-loop systems, and now agentic AI.

With AI innovation accelerating and enterprise demand growing, the next phase of the company’s journey is just beginning.

OUR TECH

What sets our platform apart

• Brand-aware AI that learns your voice, tone, and terminology to ensure every translation is accurate and consistent

• Agentic AI workflows that automate the entire translation process from content ingestion to quality review to publishing

• 100+ native integrations with systems like Adobe Experience Manager, Webflow, Salesforce, GitHub, and Google Drive to simplify content translation

• Human-in-the-loop reviews via our global network of professional linguists, for high-impact content that requires expert review

The company IN THE NEWS

• Featured in The Software Report’s [link for members] Top 100 Software Companies!

• the company makes it onto the Inc. 5000 List [link for members]

• the company’s continues to be an intellectual powerhouse, holding numerous patents [link for members] that help power the most efficient and sophisticated AI and language models in the industry.

• Check out all our news on our website [link for members]

Information collected and processed as part of your application process, including any job applications you choose to submit, is subject to the company's Privacy Policy at [link for members]

At the company, we are committed to a fair, inclusive, and transparent hiring process. As part of our recruitment efforts, we may use artificial intelligence (AI) and automated tools to assist in the evaluation of applications, including résumé screening, assessment scoring, and interview analysis. These tools are designed to support human decision-making and help us identify qualified candidates efficiently and objectively. All final hiring decisions are made by people. If you have any concerns, require accommodations, or would like to opt-out of the use of AI in our hiring process, please let us know at [link for members]

The company is an equal opportunity employer. We extend equal opportunity to all individuals without regard to an individual’s race, religion, color, national origin, ancestry, sex, sexual orientation, gender identity, age, physical or mental disability, medical condition, genetic characteristics, veteran or marital status, pregnancy, or any other classification protected by applicable local, state or federal laws. We are committed to the principles of fair employment and the elimination of all discriminatory practices.