Global Fishing Watch is looking for a Machine Learning Engineer to join their data science and engineering team. This opportunity will suit candidates with a background in data science or computer engineering who would enjoy developing models from GPS data and satellite imagery to support GFW's mission of understanding global fishing patterns and their impact on the world's oceans. GFW's technology makes data about global fishing fleets accessible and transparent in an effort to promote greater sustainability practices.
Join the Global Fishing Watch data science and engineering team. We are looking for a talented Machine Learning engineer to help us reveal human activity across the world’s oceans. The job will focus on developing and implementing models using vessel transponder (GPS) data and satellite imagery (both radar and optical). The ideal candidate will be skilled with the standard Python scientific libraries, experienced with distributed computing, and have a strong data science or computer engineering background. Full description here.
Apply with a cover letter and CV to [email protected] by Wednesday, March 18.
Location: GFW has a distributed workforce, with employees all over the world.
This position will require the individual to have a time zone that overlaps
significantly with California and Buenos Aires, with strong preference for U.S.
Pacific, Central, or Mountain time.
Responsible to: Research & Innovation Director and Technical Director
Salary or Compensation: Commensurate with experience. GFW offers
pension/retirement, health and other benefits commensurate with similar
level GFW employees in country of employment.
Working Hours: Global Fishing Watch (GFW) supports flexible working,
so the pattern of hours may vary according to operational and personal
needs. Periodic domestic and international travel will be required to meet
with team members and for workshops. No overtime is payable.
Equal opportunities: GFW is an equal opportunities employer and
commitment to this process is expected.
Global Fishing Watch (GFW) is an independent, international non-profit
organization. We are committed to advancing ocean sustainability and
stewardship through increasing transparency. We accomplish this goal by
supporting new science and research, by boosting the global dialogue on ocean
transparency, and by offering, for free, data and near real-time tracking of global
commercial fishing activity. Our ambition is to provide an unprecedented global
picture of the pattern of fishing activity.
GFW processes a global database of vessel GPS positions, several terabytes in
size. From this data, GFW has developed models that infer each vessel’s type
and size as well as when they are likely fishing. In addition to refining these
models, GFW continues to develop new models, including models to identify
suspicious behavior and unreported catch. To better understand the activity of
vessels that do not broadcast their GPS positions, we are also now analyzing
global feeds of satellite optical and radar imagery to detect vessels.
We are looking for a machine learning engineer to join our research and data
science team to develop and scale these models. This team works closely with
external GFW academic partners to develop models and research, and also with
the internal GFW engineering team to scale our methods and put them into
In collaboration with the GFW technical teams, the engineer will work with GFW’s
Senior Machine Learning Engineer to develop and implement models that
identify activity by vessels in the world’s oceans. This work involves both refining
our key existing models -- convolutional neural nets that identify vessel
characteristics and behavior from GPS positions -- and developing new models,
including both more behavior models using GPS and image detection algorithms.
Knowledge of the latest machine learning techniques is helpful but not required.
More important is a knowledge of Python, an ability to work with big data, an
ability to work productively with a remote team, and a desire to solve problems
that face the world’s oceans.
This position will work closely with both the GFW Research Team, which
develops models and partners with academics, and the GFW Engineering Team,
which implements and scales GFW’s data processing.
- Several years of experience with Python.
- Proficient with standard Python Data Science Packages of Numpy, Pandas, and Scikit Learn.
- Experience with distributed computation, such as Apache Beam (preferred), or Hadoop, Spark, etc.
- Data Science Experience or Computer engineering background.
Helpful, but can be learned on the job
- Experience with Tensorflow.
- Experience with neural networks.
Visit the Global Fishing Watch opportunity page to learn more and view other opportunities.
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