About The Role
You will be hands-on in production — owning GPU-based ASR inference systems, building backend and frontend systems, debugging failures in real time, and leading a team of engineers and interns building speech infrastructure that works every day under real customer usage.
You will make technical decisions, set the engineering standard, and be the person the team looks to when systems break. If something fails in production, you own the fix end-to-end.
If you are someone who thrives in high-ownership environments, stays calm when things break, and cares deeply about building systems that actually work — this role is for you.
What You Will Own
- Deploy and operate GPU-backed ASR inference services on AWS
- Manage latency, batching, concurrency and cost tradeoffs
- Ensure inference servers are always online and recover cleanly from failures
- Debug production issues in real time across GPU inference, audio pipelines and APIs
- Design and maintain durable JSON schemas for downstream workflows
- Design and build scalable backend APIs and microservices
- Own backend architecture decisions — database design, service structure and data flow
- Build and maintain frontend interfaces for internal tools, dashboards and client-facing products
- Set engineering standards, conduct code reviews and mentor junior team members
- Coordinate interns building country-specific semantic datasets
What You Actually Are
- You are comfortable making decisions with incomplete specs
- You document assumptions and tradeoffs without being asked
- You prioritise predictability over cleverness
- You stay calm when production breaks and fix things without waiting for permission
- You lead by example — your team follows your technical standard, not just your title
- You do not wait to be told what to do when something is wrong
Non-Negotiables
- 5+ years in backend, systems, platform or infrastructure engineering
- Hands-on production experience with GPU-based inference or ML serving
- Experience deploying and operating systems on AWS or GCP
- Built and owned real-time or near-real-time APIs
- Debugged live production systems under real user traffic
- Strong Python and Linux fundamentals
- Experience with Docker and CI/CD pipelines
- Comfortable being accountable for system behaviour, not just code
Strong Plus
- Operated GPU inference under cost and latency constraints
- Worked on speech, audio or media pipelines
- Designed or enforced data schemas in production systems
- Used infrastructure-as-code — Terraform or AWS CDK
- Built queue-based or async systems — SQS, Kafka, Redis
- Participated in on-call rotations or owned reliability metrics
- Experience with modern frontend frameworks — React, Next.js or similar
This Role Is Wrong For You If...
- You prefer research over production
- You dislike being on-call or handling outages
- You avoid debugging under pressure
- You need highly detailed specs before moving forward
- You are optimising for title, visibility or resume optics
Who Will Thrive Here
- Engineers who take full ownership of what they build and ship
- Systems thinkers who see the whole pipeline, not just their part
- Calm debuggers of complex and unexpected production failures
- Technical leaders who lead by doing, not just directing
- High-agency individuals who care about real-world impact
What You'll Get
- Up to USD 2,000 per month + meaningful ESOP
- Remote-first flexibility across Vietnam, Indonesia or India
- Direct hand in shaping the architecture and technical foundations of VALSEA
- Growth measured by system ownership and trust, not titles
- Work alongside a team built on trust, ownership and a shared mission
About VALSEA
VALSEA is speech intelligence infrastructure for Southeast Asia — built for the accents, dialects, and code-switching that every other AI ignores.
