As a member of our public sector delivery team, you will own relationships critical to the portfolio of clients charged with a layered defense for the United States. You will be a catalyst, willing to go deep, get technical, and drive change. You will manage customer relationships and partners as well as partner with our engineering team to solve Scale’s hardest problems.
Your key responsibilities will include:
- Driving innovation and transformation by diving deep into technical and operational challenges, solving undefined problems, and delivering impactful agentic AI solutions
- Transitioning AI/ML technologies and processes into working products/solutions even when requirements are undefined or ambiguous
- Partnering with Scale engineering, operations, and other public sector teams to build and deliver AI systems tailored to unique government use cases in the computer vision and generative AI domains
- Leading a cross-functional team to exceed the customer’s AI/ML objectives
- Supporting and partnering across B2B and B2G organisations to achieve the outcomes in delivering the greater layered defense for the United States
We have a diverse team with a variety of skill sets, many have:
- 5+ years of professional experience, often in a customer-facing technical program management role in industry or government
- A proven track record in B2B or government client-facing roles and expanding client relationships
- Prior experience leading engagements with government customers
Must-haves include:
- An active TS/SCI clearance
- Minimum of 3 years of work experience leading teams/programs in industry or government
- A basic understanding of ML operations process
- A track record of structured, analytics-driven problem-solving
- Excellent verbal and written communication skills
- Willingness to travel at least 25% of the time
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.
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