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Job Description:
Pluralsight is seeking a Solutions Portfolio Lead to develop, implement and manage technology learning products within our growing portfolio that today includes AI Academy, Cloud Ready, and Secure Ready. Our products support customers in meeting specific business and technical outcomes by upskilling their teams in AI, Data, Cloud, and Security. This work includes developing programs, identifying courses, labs, assessments, and live instructor\-led training. You will have a meaningful role in helping customers align employee skills with business objectives. You will own the performance and evolution of our current and future Cloud and Security solutions (e.g., Cloud Ready, Secure Ready) across strategy, roadmap, packaging, and GTM, in a matrix partnership with Product, Sales, and Marketing.
As the lead, you define the Pluralsight Expert POV. You also build the components of the solutions, including frameworks, program management, hands\-on learning, courses, instructor\-facilitated training, and more. These components make the solutions valuable to our customers. You will monitor market trends, identify customer needs, define solution offerings, leverage the expertise of Pluralsight's global network of technology experts and partners across the organization to bring differentiated, outcomes\-driven learning experiences to market for enterprise customers.
This role brings a forward\-looking perspective on emerging technical expertise and modern learning build practices, establishing Pluralsight’s offerings as credible, differentiated, and ahead of the market
What you’ll do:
- Serve as the owner of Pluralsight’s expert point of view which forms the foundation of these offerings.
- Design solution products to scope the offering, its audience, problem it addresses, business outcome it enables, structure, and milestones, ultimately providing the program design to the Curriculum team responsible for scoping the course\-level learning objectives.
- Identify frameworks, messaging, courses, hands\-on labs, and program management needed to deliver successful customer outcomes; ensure continuous delivery of value and renewal of the offering over time.
- Maintain and communicate a 12–18 month roadmap related to your solutions, including new levels, variants, and accelerators tied to market shifts in AI.
- Systematically test and iterate solution design (cohorts, format mix, level structure, assessments, services overlays) using experiments and data.
- Be responsible for solution‑level benchmarks including pipeline, win rate, adoption, and cohort completion / outcome metrics; lead a quarterly business review for your solutions.
- Partner with Sales on opportunity strategy, referenceable customer logos, and driven plays; directly support top strategic deals.
- Continuously monitor and interpret changes in technical expertise. Translate emerging enterprise skill needs into timely updates for the solutions portfolio. These updates keep Pluralsight ahead of market demand.
- Identify, engage, and work with SMEs, translating complex technical knowledge into accessible, high\-quality learning experiences.
- Represent your solutions area with executive presence and credibility. Actively engage internal collaborators, enterprise customers, SMEs, and industry audiences to build trust, drive alignment, and elevate Pluralsight's market position.
- Navigate and align across a complex, cross\-functional ecosystem of content, product, engineering, professional services, and go\-to\-market teams.
- Use data, customer feedback, and learner insights to measure program performance, identify content gaps, and drive continuous improvement of your solutions.
Requirements:
- Experience defining and launching packaged solutions (not just content) in a SaaS or services context.
- Experience in curriculum design and modern learning methodologies, with a strong understanding of how to structure learning experiences that drive measurable outcomes for professional and technical audiences.
- Experience working closely with enterprise sales to shape and close multi‑stakeholder deals.
- A deep understanding of the commercial landscape, connecting content strategy and learning design decisions to revenue growth, customer retention, and the evolving needs of enterprise buyer
- Ability to manage and prioritize across multiple programs simultaneously in a fast\-moving environment
- Strong cross\-functional collaboration skills with experience working across product, technical, consulting, and commercial teams
- Data\-informed decision\-making with the ability to use learner outcomes and engagement metrics to continuously improve program quality
- Proven experience designing and delivering blended learning programs that integrate on\-demand learning, virtual instructor\-led training, and structured program management into a cohesive, end\-to\-end learner experience.
- Deep understanding of AI technologies and how organizations adopt and operationalize technology to achieve business outcomes.
- 8\+ years of relevant background in curriculum development, instructional building, technical content development, or a related field.
- Experience working with or in support of enterprise customers, with knowledge of the ways learning solutions align with business priorities.
- Proven ability to synthesize market insights into actionable strategy and solution direction.
Why you’ll love working here:
- We work in a blended environment that supports collaboration, flexibility, and connection across teams.
- We are mission\-driven, shaping the future of tech upskillling and delivering impact that matters.
- We foster a culture of inclusion and belonging, where everyone can contribute and thrive.
- We are always learning, creating an environment where you can take on new challenges, expand your skills, and grow with purpose.
- Benefits include competitive compensation, bonus eligibility, comprehensive medical coverage, unlimited PTO, wellness reimbursement, professional development funds, and more.
About us:
Pluralsight provides the only learning platform dedicated to accelerating the technology skills and capabilities of today’s tech workforce. Thousands of companies, government organizations and individuals around the world rely on Pluralsight to support critical technology skill development in areas that are crucial to innovation including artificial intelligence, cloud computing, cybersecurity, software development, and machine learning. We offer highly curated content developed by vetted technology experts, industry leading skill assessments, and hands on, immersive learning experiences designed to help individuals skill\-up faster.
Physical Requirements:
This role is primarily performed in an office or home office setting and involves standard computer\-based work.
EEOC \& Accommodations Statement:
Bring yourself. Pluralsight is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or veteran status. We also consider qualified applicants with criminal histories, consistent with EEOC guidelines and local laws.
If you need an accommodation to apply, interview, or perform essential job functions,
*Pay Transparency:*
*The annual US base salary range for this role is $110,200\- $145,000 USD. Actual compensation will depend on location, skills, experience, and other factors. Additional benefits and bonuses may apply.*
*Applications must be submitted within 90 days after the initial posting date to be considered.*
*Recruiting Scam Notice:*
*Please be aware of recruiting scams. We’ll only contact you from an @pluralsight.com email or verified channels. We never ask for sensitive personal info or payments as part of the hiring process. All openings are posted on our Careers page.*
*\#LI\-SD1*
*\#LI\-Remote*
### About Us
Pluralsight provides the only learning platform dedicated to accelerating the technology skills and capabilities of today’s tech workforce. Thousands of companies, government organizations, and individuals around the world rely on our platform to support critical technology skill development in areas that are crucial to innovation, including artificial intelligence, cloud computing, cybersecurity, software development, and machine learning.
We offer highly curated content developed by vetted technology experts, industry leading skill assessments, and hands\-on, immersive learning experiences designed to help individuals skill\-up faster.
Salary Context
This $110K-$145K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Pluralsight, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($127K) sits 42% below the category median. Disclosed range: $110K to $145K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Pluralsight AI Hiring
Pluralsight has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $145K - $220K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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