MasterClass
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Staff AI / ML Engineer
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Who we are:
MasterClass is the streaming platform where the world’s best come together so anyone, anywhere, can access and be inspired by their knowledge and stories. We put you in the room with the creators, thinkers, makers and leaders who have changed the world, so that you can change yours.
Members get unprecedented access to 200+ instructors and classes across a wide variety of fields, including Arts & Entertainment, Business, Design & Style, Sports & Gaming, Writing and more. Step into Nas’ recording studio and Gordon Ramsay’s kitchen, and go behind the big screen with James Cameron. Design your career with Elaine Welteroth, get ready to win with Lewis Hamilton, perfect your pitch with Shonda Rhimes and discover your inner negotiator with Chris Voss.
We’re a remote-first workforce with collaborative work spaces in San Francisco and Kitchener, Ontario, and employees in several U.S. states. If you’re interested in joining a dynamic, culture-driving company—where learning invaluable skills is all in a day’s work—we invite you to apply.
Snapshot of the Role:
MasterClass is building the next generation of learning products with AI at the core. Foundation models and agentic systems are central to how we design and deliver every new product, powering intelligent, adaptive experiences that help millions of people learn from the world's best. This is not a side initiative. It is the direction of the company.
We are looking for a Staff ML Engineer to join our AI engineering team and help define and deliver these products. This role is ultimately about delivery. You will be expected to stay deeply connected to the latest research, models, and techniques, but the measure of success is shipping products that people use. You will work alongside a small, talented group of ML engineers and partner closely with product, design, and engineering leadership to shape what AI-powered learning looks like at MasterClass.
What You Will Do:
- Design and build agentic AI systems that power consumer learning products, including multi-step reasoning, tool use, and orchestration architectures.
- Select and integrate foundation models (LLMs, multimodal) based on product requirements, making pragmatic trade-offs between quality, latency, cost, and safety.
- Build evaluation and observability frameworks that ensure AI product quality at scale, including automated testing, human-in-the-loop review, and production monitoring.
- Architect reliable, production-grade AI pipelines, including prompt management, context retrieval (RAG), caching, and fallback strategies.
- Collaborate with Product, Design, and Engineering to translate ambiguous product goals into well-defined technical approaches and ship features end-to-end.
- Stay deeply current with the foundation model landscape—new models, techniques, agentic frameworks, and research—and bring that knowledge to bear on product decisions.
- Mentor and elevate the AI engineering team by sharing best practices, leading design reviews, and establishing reusable patterns for agentic product development.
About You (Requirements):
- 7+ years of software engineering experience, with 3+ years focused on building products with large language models or foundation models.
- Demonstrated experience shipping consumer-facing AI products that use agentic patterns (tool use, multi-step reasoning, orchestration, planning).
- Deep working knowledge of the current foundation model ecosystem: model providers (OpenAI, Anthropic, Google, open-source), prompt engineering, RAG architectures, evaluation frameworks, and orchestration tooling.
- Strong software engineering fundamentals: system design, API design, production observability, and the ability to write clean, maintainable code in Python.
- Track record of staying on the cutting edge—you can point to specific ways you’ve incorporated new research, models, or techniques into shipped products.
- Excellent collaboration and communication skills; experience working cross-functionally with product, design, and engineering teams.
Nice To Haves
- Experience with model fine-tuning or distillation (SFT, DPO, RLHF).
- Background in edtech, consumer media, or content platforms.
- Published research or open-source contributions in AI/ML.
- Experience with multi-agent system design or advanced orchestration frameworks.
Nice-to-haves are not required; each represents a direction in which our infrastructure is evolving.
At MasterClass, we believe we put our best work forward when our employees bring together ideas that are diverse in thought. We are proud to be an equal opportunity workplace and are committed to equal employment opportunity regardless of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or any other characteristic protected by applicable federal, state or local law. In addition, MasterClass will provide reasonable accommodations for qualified individuals with disabilities. If you have a disability or special need, we would like to know how we can better accommodate you.
The salary range listed is for candidates in Ontario, Canada. As a company, we have a location based strategy, which means the disclosed range estimate has been adjusted for geographic differential associated with the location where the position may be filled.
MasterClass’s salary ranges are based on paying competitively for our size and industry. In addition to salary, we also offer equity and comprehensive benefits (medical, dental, vision, flexible PTO, and more). The range listed is for the expectations as laid out in the job description, however we are often open to a wide variety of profiles, and recognize that the person we hire may be less experienced (or more senior) than this job description as posted. If that ends up being the case, the updated salary range will be communicated with you as a candidate.
Ready to apply?
Apply to MasterClass
Staff Software Engineer, Infrastructure
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Who we are:
MasterClass is the streaming platform where the world’s best come together so anyone, anywhere, can access and be inspired by their knowledge and stories. We put you in the room with the creators, thinkers, makers and leaders who have changed the world, so that you can change yours.
Members get unprecedented access to 200+ instructors and classes across a wide variety of fields, including Arts & Entertainment, Business, Design & Style, Sports & Gaming, Writing and more. Step into Nas’ recording studio and Gordon Ramsay’s kitchen, and go behind the big screen with James Cameron. Design your career with Elaine Welteroth, get ready to win with Lewis Hamilton, perfect your pitch with Shonda Rhimes and discover your inner negotiator with Chris Voss.
We’re a remote-first workforce with collaborative work spaces in San Francisco and Kitchener, Ontario, and employees in several U.S. states. If you’re interested in joining a dynamic, culture-driving company—where learning invaluable
skills is all in a day’s work—we invite you to apply.
Snapshot of the Role:
We’re looking for a Staff Infrastructure Engineer who operates as a technical leader and force multiplier across the platform. This is a senior individual contributor role for someone who designs systems that scale beyond a single team, sets technical direction, and elevates how infrastructure is built and operated across MasterClass.
You’ll lead and provide direction for cloud infrastructure, developer platforms, video infrastructure, and emerging AI/ML infrastructure—partnering closely with product engineering, content production, data, and AI teams. This role is ideal for someone who combines deep systems expertise with strong software engineering, thrives in ambiguity, and takes ownership from strategy through execution.
This is not a people-management role, but it carries significant technical leadership responsibility.
What You Will Do:
- Set technical direction for core infrastructure systems, balancing reliability, scalability, security, and developer velocity.
- Design and lead implementation of complex, cross-team infrastructure initiatives (AWS, EKS, CI/CD, shared platforms).
- Build production-grade software to power infrastructure automation, tooling, and internal platforms.
- Drive org-wide improvements in observability, incident response, reliability engineering, and cost efficiency.
- Lead video infrastructure initiatives to evolve video delivery and CDN strategies for global scale and performance.
- Partner with AI and Data teams to define and build GPU-powered infrastructure, model-serving platforms, and GenAI inference/training workflows.
- Act as a technical mentor and reviewer, raising the bar for infrastructure design and operational excellence across teams.
- Lead by example during incidents, postmortems, and critical architectural decisions.
About You (Requirements):
- 10+ years building and operating cloud-native production systems.
- Strong expertise in:
- AWS architecture and large-scale cloud operations
- Kubernetes / EKS (networking, RBAC, Helm, autoscaling, cluster-level debugging)
- Infrastructure as Code (Terraform preferred)
- CI/CD and automation (GitHub Actions, Argo, or similar)
- Proven ability to design and build infrastructure software, not just operate systems.
- Deep understanding of distributed systems, networking, Linux internals, and cloud security.
- A track record of driving step-function improvements in reliability, scalability, or developer experience.
- Strong written and verbal communication skills; able to influence technical decisions across teams.
Who You Are
- You think in systems and leverage, not just tasks.
- You care deeply about craftsmanship, clarity, and long-term maintainability.
- You enjoy solving ambiguous, cross-functional technical problems.
- You’re pragmatic—you optimize for impact over novelty.
- You raise the bar through mentorship, design reviews, and thoughtful collaboration.
- You’re energized by both strategic architecture and hands-on implementation.
Nice To Haves
- AI/ML infrastructure, GPU scheduling, or distributed training
- Model serving frameworks (e.g., Triton, vLLM, TensorRT-LLM)
- Infrastructure autoscaling strategies, including application workloads, databases, and GenAI workloads
- KEDA, Karpenter, service mesh, or multi-cluster architectures
- HLS/DASH packaging or video encoding pipelines
Nice-to-haves are not required; each represents a direction in which our infrastructure is evolving.
At MasterClass, we believe we put our best work forward when our employees bring together ideas that are diverse in thought. We are proud to be an equal opportunity workplace and are committed to equal employment opportunity regardless of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or any other characteristic protected by applicable federal, state or local law. In addition, MasterClass will provide reasonable accommodations for qualified individuals with disabilities. If you have a disability or special need, we would like to know how we can better accommodate you.
The salary range listed is for candidates in Ontario, Canada. As a company, we have a location based strategy, which means the disclosed range estimate has been adjusted for geographic differential associated with the location where the position may be filled.
MasterClass’s salary ranges are based on paying competitively for our size and industry. In addition to salary, we also offer equity and comprehensive benefits (medical, dental, vision, flexible PTO, and more). The range listed is for the expectations as laid out in the job description, however we are often open to a wide variety of profiles, and recognize that the person we hire may be less experienced (or more senior) than this job description as posted. If that ends up being the case, the updated salary range will be communicated with you as a candidate.
Ready to apply?
Apply to MasterClass