ML Team Lead
About the Role
You will lead the applied ML team at VALSEA, owning the quality, direction and delivery of speech intelligence across SEA languages, accents and real-world audio conditions. This is not a research role and it is not a pure management role. You will be hands-on in production while setting the technical direction and raising the bar for the team around you.
If you thrive at the intersection of research depth and shipping velocity, and you want to own a problem that affects how machines understand how billions of people actually speak — this role is for you.
What You Will Own
Set the technical direction for ML and speech model development across SEA languages and accents
Lead, mentor and grow a team of ML engineers and interns
Own the quality of speech outputs in production — accuracy, robustness, latency and cost
Drive the team from experiments to deployed improvements without losing momentum
Define evaluation standards, experiment frameworks and model quality benchmarks
Collaborate with engineering to integrate models into production pipelines
Identify systemic failure modes across languages and audio conditions and drive solutions
Build a culture of ownership, initiative and rigorous experimentation within the team
What This Role Is Really About
You are not here to manage a research lab.
You are here to:
Lead a team that ships measurable improvements to real production speech systems
Raise the technical bar while keeping the team moving fast
Make decisions under uncertainty — messy data, evolving requirements, incomplete signals
Be the person who finds model failures before customers do
Translate business needs into ML strategy and ML results into business impact
What We Expect From You
Leadership
You set clear technical direction without micromanaging
You give direct, honest feedback and make the team better for it
You unblock engineers and remove friction from the path to shipping
You hire and develop talent with high standards and low ego
You represent the ML team's work clearly to founders and stakeholders
Founding Mindset
You think in shipped improvements, not paper metrics
You ask how will this behave in production before trying a new approach
You act like speech quality is your personal responsibility
You balance research depth with shipping velocity
You do not wait for others to point out model failures — you go find them
Maturity
You communicate clearly about what is known, unknown and risky
You admit when an experiment failed and extract learning from it
You stay calm under pressure when models behave unexpectedly in production
You follow through on investigations into failure modes
What We're Looking For
4+ years in applied ML or speech engineering with at least 1–2 years leading a team
Strong Python and PyTorch fundamentals
Deep understanding of ASR, speech processing and evaluation methods
Experience shipping ML models into real production systems
Familiarity with GPU inference, optimisation workflows and production constraints
Ability to define and enforce evaluation standards across a team
Strong communicator — can translate between research, engineering and business
Strong Plus
Experience with multilingual or low-resource speech — especially SEA languages
Exposure to on-device or low-latency inference
Experience building evaluation pipelines and annotation workflows
Background in code-switching, accent robustness or noisy audio scenarios
What Success Looks Like
Your team ships at least one measurable improvement per sprint across accuracy, robustness or latency
You establish clear evaluation standards and experiment documentation practices
You identify and resolve systemic failure modes across languages and audio conditions
You develop team members who take increasing ownership over time
Who Will Thrive Here
Technical leaders who lead by doing, not just directing
Builders who love shipping ML to production
Systems thinkers who see the whole pipeline, not just the model
High-agency individuals who hold themselves accountable for real-world impact
Who Should Not Apply
If you prefer managing without staying technically sharp
If you avoid messy data and hard debugging
If you prefer purely research environments detached from production
If you need complete specifications before making decisions
What You'll Get
Full ownership of ML direction at a speech intelligence company built for SEA
Direct collaboration with founders and senior engineers
A team to lead and develop from the ground up
Meaningful equity aligned with your impact
Remote-first flexibility
This is an equity-only role. No salary is provided at this stage.
About VALSEA
We're building the speech intelligence layer for Southeast Asia — turning real-world, accented, code-switched speech into structured, usable outputs for businesses.
- Locations
- Singapore, APAC
- Remote status
- Fully Remote