VINFAST is a pioneering electric vehicle (EV) company committed to revolutionizing the automotive
industry with sustainable and innovative mobility solutions. As a leading player in the EV market,
VinFast is dedicated to delivering high-quality, cutting-edge electric vehicles that redefine the driving
experience. Our team consists of passionate professionals driven by a shared vision of creating a greener and
more sustainable future through innovation, technology, and excellence.

In this role, y
ou will
be responsible for
building
scalable, searchable, and version-controlled data infrastructure
that
em
powers machine learning pipelines for autonomous driving systems.
Y
our work will
facilitate
model training and contribute to
achieving
high
level of
performance and generalization of our
advanced
ML models
.

• 
  Design and implement data lake
  s
  as a
  flexible and scalable
  storage of
  sensor data

• 
  Build scalable pipelines
  for
  indexing
  raw and extracted sensor data

• 
  Develop
  searchable database
  s
  for
  efficient
  information retrieval

• 
  Implement robust ETL pipelines to extract, transform, and load data into a structured data warehouse

• 
  Establish automated systems for data validation and quality assurance
  for large
  multi-modal datasets

• 
  Build tools for indexing and version
  control
  of extracted sensor data

• 
  Integrate
  labeling workflows
  into
  a
  data loop
  (
  s
  emi
  -
  a
  utomatic
  ,
  active learning, crowdsourcing etc.
  )

• 
  Collaborate with algorithm and software engineering teams to ensure data integrity, traceability, and reproducibility

• 
  MSc/BSc degree with 5+ years of industrial experience in Computer Science, Machine Learning, Robotics and/or similar technical field

• 
  Proficiency
  in
  Python
  and
  strong software engineering
  skills

• 
  C
  omfortable
  in
  building
  data
  processing pipelines
  tailored for
  ML
  training pipelines

• 
  K
  nowledge of
  (at least one) of the
  Parquet, Pandas, Spark
  frameworks

• 
  Solid
  understanding of
  the
  main
  sensor modalities
  for
  self-driving
  (
  cameras, L
  i
  DAR,
  radar, GPS)

• 
  Experience with
  establishing
  dataset
  version control

• 
  Familiarity with
  cloud job orchestration
  ,
  monitoring, and instrumentation best-practices

• 
  Ability to solve hard problems and handle large amounts of heterogeneous data