Applied AI Engineer, Learning Intelligence

United States Digital Space LLC; United States; On-site; USD 139,000 - 191,050; Full time

Job summary

United States Digital Space LLC is seeking an Applied AI Engineer, Learning Intelligence to own the skill and concept graph and develop ML models that infer learner capabilities. You will ship AI-driven features with explainability and collaborate with frontend engineers to ensure correct integration.

You will partner with product and content teams to validate recommendations, monitor model performance in production, and help steer the next generation of personalized learning experiences for

Qualifications

• 5+ years of experience in applied ML or data science with production recommendation or personalization systems
• Hands-on experience with knowledge graphs, graph databases, or ontology design
• Experience with LLM APIs and prompt engineering for generative features
• Hands-on history of shipping LLM-based systems to production, including large-scale deployment, evaluation frameworks, and agentic workflows
• Advanced Python proficiency and experience architecting robust, production-grade applications
• Deep familiarity with the modern AI stack, from retrieval and agent frameworks to complex prompt engineering, model evaluation, and context engineering
• A high degree of intellectual curiosity and the ability to find elegant, straightforward solutions
• Exceptional communication skills, with the ability to translate technical logic for varied stakeholders

Responsibilities

• Design, build, and maintain a skill and concept graph that maps relationships between skills, roles, domains, and learning content
• Develop ML models that infer learner skill levels from usage patterns, work output, assessments, and profile data (not just self-reported input)
• Build and iterate on recommendation systems that surface the next best module, suggest learning paths, and generate content dynamically
• Partner with frontend engineers to ensure AI outputs are consumed correctly, surfaced with appropriate context
• Define explainability standards for model outputs so users and stakeholders understand why a recommendation was made
• Collaborate with product and content teams to validate recommendation quality and close feedback loops
• Monitor model performance in production and own the evaluation framework for recommendation quality

Skills

Applied ML

Knowledge graphs

LLM APIs

Prompt engineering

Python

Production systems

Communication

Tools

Graph databases

Ontology design

Job description

CSQ227R13

Applied AI Engineer, Learning Intelligence

About the Role

We are building the intelligence layer that powers how learners grow. This role sits at the intersection of machine learning, knowledge representation, and product engineering. You will own the skill and concept graph that defines what learners know and can do, infer skill gaps from behavioral and profile signals, and translate those inferences into personalized recommendations and dynamic learning that guide each learner to their next best step. You will also be the bridge between our AI capabilities and the engineers building our frontend, making sure AI-driven features ship in a way that is explainable, reliable, and production-ready.

What You Will Do

• Design, build, and maintain a skill and concept graph that maps relationships between skills, roles, domains, and learning content
• Develop ML models that infer learner skill levels from usage patterns, work output, assessments, and profile data (not just self-reported input)
• Build and iterate on recommendation systems that surface the next best module, suggest learning paths, and generate content dynamically
• Partner with frontend engineers to ensure AI outputs are consumed correctly, surfaced with appropriate context
• Define explainability standards for model outputs so users and stakeholders understand why a recommendation was made
• Collaborate with product and content teams to validate recommendation quality and close feedback loops
• Monitor model performance in production and own the evaluation framework for recommendation quality

What We Are Looking For

• 5+ years of experience in applied ML or data science, with production recommendation or personalization systems in your background
• Hands‑on experience with knowledge graphs, graph databases, or ontology design
• Experience with LLM APIs and prompt engineering for generative features
• Hands‑on history of shipping LLM-based systems to production, including large‑scale deployment, evaluation frameworks, and agentic workflows
• Advanced Python proficiency and experience architecting robust, production‑grade applications
• Deep familiarity with the modern AI stack, from retrieval and agent frameworks to complex prompt engineering, model evaluation, and context engineering
• A high degree of intellectual curiosity and the ability to find elegant, straightforward solutions
• Exceptional communication skills, with the ability to translate technical logic for varied stakeholders

Pay Range Transparency

The company is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non‑commissionable roles or on‑target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job‑related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, the company anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range: $139,000 — $191,050 USD

Zone 2 Pay Range: $125,000 — $171,950 USD

Zone 3 Pay Range: $118,100 — $162,350 USD

Zone 4 Pay Range: $111,200 — $152,900 USD

Benefits

At the company, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At the company, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at the company are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio‑economic status, veteran status, and other protected characteristics.

Compliance

If access to export‑controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.