RAMZ / CAREERS
Careers at
RAMZ AI.
Role descriptions in applied AI, machine learning, research, software engineering, language evaluation, design and go-to-market.
View roles ↓ROLES
Responsibilities
and experience.
Applied AI, machine learning and go-to-market are the initial areas of focus. Other disciplines would grow with the research and product work.
01Applied AIAI EngineerInitial focus
Turn language models, retrieval and speech tools into useful workflows people can inspect and trust.
Responsibilities
- Build source-grounded answers, transcript review and controlled tool-use workflows.
- Design evaluations around real tasks, including failure cases and human review.
- Measure quality, latency and operating cost before expanding a capability.
Relevant experience
Python or TypeScript, practical model integration, retrieval systems and evaluation. Show a working project and explain where it fails, not just where it succeeds.
02Models & infrastructureMachine Learning EngineerInitial focus
Make speech and language experiments reproducible, measurable and practical to operate.
Responsibilities
- Build reproducible training, adaptation and inference pipelines with documented model origins.
- Evaluate transcription quality across permitted datasets, accents and code-switching.
- Profile serving performance, memory and cost under realistic deployment constraints.
Relevant experience
Python, PyTorch, dataset handling and model evaluation. Experience with speech systems, efficient inference or low-resource languages would be relevant.
03Commercial & partnershipsGTM & Partnerships LeadInitial focus
Find the practical problems worth solving and help shape a focused path from discovery to useful pilots.
Responsibilities
- Talk with prospective media, education and service teams to understand their workflows.
- Define pilot outcomes, acceptance criteria and a way to assess willingness to pay.
- Develop clear positioning, responsible outreach and partnerships grounded in actual capability.
Relevant experience
Customer discovery, early-stage B2B sales or partnerships. Bring evidence of understanding a customer problem and turning that understanding into a clear commercial proposal.
04ResearchResearch EngineerAs the work grows
Connect low-resource language research with experiments that can be reproduced and evaluated.
Responsibilities
- Investigate speech recognition, multilingual adaptation and retrieval methods.
- Build baselines, analyze failures and document data permissions and limitations.
- Prepare clear experiment reports and releasable research artifacts when ready.
Relevant experience
Strong experimental reasoning, Python and familiarity with modern ML research. Reproducible projects and careful analysis matter alongside academic experience.
05Product engineeringFull-stack Product EngineerAs the work grows
Build the interfaces and services that make a complex AI workflow feel clear and dependable.
Responsibilities
- Create accessible transcript review, source inspection and workspace interfaces.
- Build documented APIs, permission boundaries and reliable data handling.
- Ship small, complete product improvements and validate them with users.
Relevant experience
TypeScript, React, backend APIs and relational databases. Demonstrate a complete product flow, including its error states and accessibility considerations.
06Language & data qualityLanguage & Evaluation SpecialistAs the work grows
Help define what useful, respectful language support means—and how to recognize when a system falls short.
Responsibilities
- Shape evaluation criteria for language variation, transcription and locally relevant tasks.
- Review permitted examples, annotation guidance and important error patterns.
- Work with engineers on research questions, not only data labeling.
Relevant experience
Language expertise relevant to the roadmap, careful written review and an interest in evaluation. Technical or research experience can help, but community and domain expertise also matter.
07Design & user researchProduct DesignerAs the work grows
Make review, evidence and user control central to the experience from the first useful product.
Responsibilities
- Study real workflows and prototype clear paths from recordings to reviewed knowledge.
- Design multilingual, accessible interfaces and understandable limitations.
- Work with engineers to turn user feedback into focused product decisions.
Relevant experience
Interaction design, user research and accessible product design. Show the reasoning behind your portfolio, including what changed after feedback.
APPLICATION
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RESEARCH AND PRODUCT CONTEXT
Read the
research agenda.
The research agenda describes the questions and proposed outputs behind these roles. The Lab page explains the approach to data and evaluation.