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Inkling Jobs (NOW HIRING)

Mosaic.tech

Software Engineer, Product

San Francisco, CA · On-site

$300 - $475/hr

We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building ...

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Thinking Machines Lab

HR Business Partner

San Francisco, CA · On-site

$190K - $300K/yr

We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building ...

Mosaic.tech

Product Manager - Deployment

San Francisco, CA · On-site

$300 - $450/hr

We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building ...

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Inkling information

What is an Inkling?

Inkling jobs typically refer to positions at Inkling, a company that provides a cloud-based digital learning platform designed for businesses. Employees at Inkling may work in a variety of roles such as software development, customer support, product management, instructional design, and sales. These roles focus on creating, managing, and supporting digital training solutions for clients. Working at Inkling often involves collaborating with cross-functional teams to deliver innovative learning experiences to enterprise customers.

What skills and qualifications are needed to thrive as an Inkling technical writer?

To thrive as an Inkling technical writer, you need strong writing, editing, and instructional design skills, often backed by a relevant degree or experience in content development. Familiarity with the Inkling platform, content management systems (CMS), and markup languages like XML or HTML is typically required. Attention to detail, adaptability, and collaboration are crucial soft skills for creating engaging, accurate, and user-friendly digital documentation. These competencies ensure the production of high-quality, interactive content that meets organizational and user needs.

What are common challenges faced by instructional designers at Inkling, and how can they be overcome?

Instructional designers at Inkling often encounter challenges such as adapting content to evolving digital formats, collaborating across departments, and meeting tight project deadlines. Success in this role involves staying current with learning technologies, maintaining clear communication with subject matter experts, and leveraging Inkling's collaborative tools for efficient content creation. Regular feedback sessions and proactive project management can help address these challenges and ensure high-quality deliverables.

What is the difference between Inkling vs Instructional Designer?

AspectInklingInstructional Designer
Required CredentialsTypically a background in instructional technology, e-learning tools, or related fieldsOften holds degrees in education, instructional design, or related disciplines
Work EnvironmentPrimarily digital, creating interactive e-learning contentCan be digital or classroom-based, designing curricula and learning experiences
Employer & Industry UsageUsed by e-learning companies, corporate training, and educational institutionsEmployed across education, corporate training, and government sectors
Common Search & ComparisonYesYes

While Inkling focuses on creating interactive digital learning content, Instructional Designers develop comprehensive curricula and training programs, often combining digital and traditional methods. Both roles require a background in education or technology, but Inkling specialists are more tech-centric, whereas Instructional Designers have broader instructional planning expertise.

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Cities with the most Inkling job openings:

What states have the most Inkling jobs?

States with the most job openings for Inkling jobs include:

What job categories do people searching Inkling jobs look for?

The top searched job categories for Inkling jobs are:

Inkling jobs near you
Infographic showing various Inkling job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Physical job distribution.

Product Manager - Deployment

Thinking Machines Lab

San Francisco, CA • On-site

$300K - $450K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 10 days ago

Key responsibilities

  • Own deployment strategy, roadmap, and success metrics for models and checkpoints transitioning into production.

  • Define deployment workflows, including model serving, autoscaling, versioning, rollback, monitoring, and incident response.

  • Work on engineering aspects of serving architecture, latency and cost tradeoffs, reliability, capacity planning, and deployment APIs.

Job description

About Thinking Machines
The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.
About the Role
As Product Manager for Deployment, you will own how Thinking Machines' models and fine-tuned checkpoints go from training into production use. You will shape the path from a trained model to a served, reliable, cost-effective endpoint - covering inference infrastructure, serving APIs, latency and throughput tradeoffs, scaling behavior, observability, and the workflows researchers and external users rely on to deploy their work with confidence.
This is not a mature MLOps role at an established platform. Deployment at Thinking Machines is still being defined: what "production-ready" means for a fine-tuned model, which serving paths we support, how much control users get over performance and cost tradeoffs, and how we scale reliably as usage grows. You will work from infrastructure capability through to a deployment experience that is fast, predictable, and trustworthy.
The strongest candidate has shipped and operated production ML or infrastructure systems before, ideally as an engineer before becoming a product leader, and can reason from strategy down to autoscaling behavior, latency budgets, rollout safety, and the on-call realities of running models in production.
What You'll Do
  • Own deployment strategy, roadmap, and success metrics for taking models and Tinker-trained checkpoints into production, in close partnership with infrastructure, research, engineering, and GTM
  • Define priority deployment paths and workflows across model serving, autoscaling, versioning, rollback, monitoring, and incident response
  • Work at engineering depth on serving architecture, latency and cost tradeoffs, reliability targets, capacity planning, and API/SDK surfaces for deployment
  • Build direct feedback loops with users deploying models in production, and turn scattered signals into a clear view of what's broken, what's missing, and what to prioritize next
  • Drive ambiguous workstreams end to end: technical scoping, dependency resolution, launch readiness, on-call/escalation design, and post-incident learning
  • Connect deployment decisions to the model and infrastructure roadmap, making visible the tradeoffs between flexibility, reliability, and operational cost
  • Shape SLAs, pricing/packaging inputs for hosted inference, and the operating model for a deployment platform expected to scale quickly
  • Do whatever work makes deployment succeed - reviewing a serving config, joining an incident retro, inspecting latency data, or writing the rollout plan for a new model

Skills and Qualifications
  • Experience owning a production ML serving, infrastructure, or deployment product, with direct involvement in reliability, scaling, or performance decisions
  • Track record working at engineering depth with production systems - comfortable discussing latency, throughput, autoscaling, rollback, or incident response in specifics
  • Experience taking a technical product from early usage through to reliable, scaled production use

Preferred qualifications:
  • Background as an engineer or technical founder before moving into product leadership
  • Experience with ML inference infrastructure specifically (model serving frameworks, GPU scheduling, batching, quantization tradeoffs, or similar)
  • Experience operating in a startup, lab, or new product area where the deployment model and roadmap weren't handed to you
  • Comfortable moving between a strategic narrative and a specific technical detail (an autoscaling policy, an SLA definition, a rollout gate) without losing judgment
  • Experience building trust with technical users through evidence, responsiveness, and follow-through rather than process ownership

Logistics
  • Location: This role is based in San Francisco, CA.
  • Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $300,000 - $450,000 USD.
  • Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
  • Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

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