Scale's customer base is growing exponentially, and you will be on the front lines of ensuring that these customers become passionate, lifelong Scale partners. As a member of our Engagement Management team, you’ll be accountable for establishing customer relationships, identifying new project opportunities, driving revenue, hitting delivery SLAs, and maintaining quality standards. You will work closely with Scale’s Gen AI customers, owning end-to-end engagements from identifying new opportunities through overseeing operations and delivery of all ongoing projects.
You are the forefront of Scale’s contact with our Gen AI customers, working with and being an advocate for customer data leaders and engineering/operations teams. You have a strong interest in and understanding of how high-quality data can influence the development of Gen AI models. You are the voice of the customer, responsible for the execution of customer projects. Within Scale, you will work cross-functionally with Operations, Delivery, Finance, Product and Leadership to ensure that project execution and delivery is aligned with customer expectations.
The blend of operations and customer management needed to drive our most important outcomes make this a unique and exciting role at the heart of Scale’s GenAI operations. The ideal candidate is customer-driven, analytical, outcome-focused, data-oriented, and above all someone who drives and inspires results.
You will:
- Build and drive some of our most critical operational processes: the consistent, on-time delivery of Scale product and services, and revenue consumption for our customers
- Manage the long-term health of customers by identifying areas of risk or concern and advocating for them within Scale
- Review, track and improve operational performances and be obsessed with continuous improvement
- Oversee on-boarding and successful execution and ramp for new data projects
- Work directly with customer's engineering teams on project scoping, implementation and resolving blockers, partnering when needed with customer-facing MLEs and Field Engineering at Scale
- Create an effective feedback loop between the front line, product, strategy, and customers
Ideally you'd have:
- 4+ years of work experience, with experience in consulting or as a technical product or program management role in industry
- A technical background (education or professional experience with CS, Economics, Statistics, Engineering or STEM field)
- A proven track record in B2B client facing roles and building and expanding client relationships
- Ability to understand the ML training lifecycle and build great relationships with technical customers
- Great cross-functional experience and collaborative ability
- Excellent verbal and written communications
- A track record of structured, analytics-driven problem solving
- A history of diligence and organization across multiple work streams
- An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results
Nice to haves:
- Experience with reading SQL and/or another database language
- Graduate degree (PhD, MS) in a STEM field
- Work experience in a high-growth environment
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$140,000—$175,000 USD
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an affirmative action employer and inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
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What We Do
Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.