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Job Machine Learning Engineer Sensing en Remote

Global Fishing Watch en Washington, District of Columbia, United States

Digital job Machine Learning Engineer Sensing at Global Fishing Watch

Machine Learning Engineer Sensing

Global Fishing Watch Washington, District of Columbia, United States

$60,000 - $100,000

Remote Full-time
Development 2-5 años Docker Python Cloud System
By Remote Ok
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Job description

Background: Global Fishing Watch is an international, non-profit organization committed to advancing ocean governance through increased transparency. We create and publicly share knowledge about human activity at sea to enable fair and sustainable use of our ocean. Founded in 2015 through a collaboration between Oceana, SkyTruth, and Google, GFW became an independent non-profit organization in 2017. Using cutting-edge technology, we create and publicly share map visualizations, data and analysis tools to enable scientific research and drive a transformation in how we manage our ocean. By 2030, we aim to monitor and map all commercial activity at sea, including all industrial fishing vessels, small-scale fishing activity, all large non-fishing vessels, and all fixed infrastructure such as aquaculture and oil rigs. We also plan to work with intergovernmental organizations and 30 governments around the globe to promote the adoption of transparency more widely and publicly share ocean data to drive better management of marine resources.

The Position

The Research and Innovation team at Global Fishing Watch (GFW) connects data science and machine learning experts with the scientific community to produce new datasets, publish impactful research, and empower others to use our data. This team harnesses satellite technology, machine learning, and big data to shed light on some of the most pressing issues facing the ocean.

We are now working to map the global footprint of commercial activity at sea, including the activity of all ocean-going vessels and fixed infrastructure. This work involves combining deep learning and data fusion techniques with petabytes of satellite imagery (radar and optical), and billions of GPS positions from vessels, mostly from the Automatic Identification System (AIS) and Vessel Monitoring Systems.

The Machine Learning Engineer will assist with large data pipelines of satellite imagery and help build computer vision models to detect and classify maritime objects in imagery data. The initial focus will be on vessel detection in high-resolution (3 m) PlanetScope optical imagery from Planet Labs, leveraging an existing model architecture developed for Sentinel-2. Subsequent work includes implementing new models to expand the detection capability to offshore infrastructure using new satellite imagery sources. The candidate will also collaborate closely with other members of the Research and Innovation team to correlate detected vessels (position, time and length) to vessels tracked by AIS. Finally, the candidate will work closely with the GFW Engineering and Product teams to ensure solutions are compatible and scalable within our cloud infrastructure. 

The incumbent will gain experience working with leading researchers in the field and will interface daily with GFW’s team of data scientists and machine learning experts. They will develop further technical skills in programming, big data, and cloud computing while working for a globally diverse and fully distributed organization. The successful candidate will be organized and excited to help Global Fishing Watch develop strong partnerships and cutting-edge research. 

Principal Duties and Responsibilities

Model development for small object detection

  • Design, train, and evaluate computer vision models for object detection in satellite imagery, with an emphasis on vessel detection in optical imagery 
  • Implement preprocessing pipelines to obtain imagery and prepare it for annotation and modelling 
  • Devise annotation strategies and tools for labelling vessels and fixed infrastructure in satellite images
  • Improve our training datasets and build new training datasets for other human-made objects, potentially managing external annotation services

Additional tasks may include

  • Provide technical support to the senior machine learning engineer(s) responsible for developing and advancing other Global Fishing Watch models
  • Assist data fusion efforts to integrate detections from multiple sources (e.g. Sentinel-1 SAR and Sentinel-2 optical), accounting for the recall of each model, length of the objects, cloudiness, and image resolution, among others
  • Analyze large amounts of data from various sources, such as vessel tracking, identity, and satellite imagery to identify trends, anomalies, and insights
  • Ensure the integrity and accuracy of key data pipelines and research BigQuery tables 
  • Maintain and improve internal Python tools, such as modules and template repositories, to assist with migrating research projects from proof-of-concepts to automated prototypes
  • Lead or support eventual research publications and technical blog posts

Candidate description

Skills you should have

  • Bachelor's degree and at least four years of professional experience, or an equivalent combination of education and experience, in physical/earth sciences or a related field
  • Demonstrated skills and experience with Python
  • Strong foundation in mathematics and statistics
  • Familiarity working with geospatial data
  • Demonstrated experience working with cloud compute platforms and virtualized environments
  • Self-motivated with a strong curiosity and desire to learn new skills
  • Willingness to take ownership of projects and communicate project updates
  • Written and verbal communication skills in English
  • Ability to work with a remote team and embrace Slack, Google Suite, Jira, Notion and other collaborative tools

Also great

  • Some experience with database query languages such as SQL
  • Demonstrated experience with computer vision models
  • Demonstrated experience with frameworks such as TensorFlow or PyTorch
  • Familiarity with containerization tools like Docker and execution of models inside them
  • An appreciation for the complexities and rewards of collaborating in a remote, global and inclusive environment
  • Experience engaging with academic researchers and the peer-review process
  • Awareness of ethical considerations related to privacy and bias in satellite imagery analysis

The successful candidate will meet most, but not necessarily all, of the criteria above. Although it is obviously helpful, we do not expect that you already have a deep knowledge of building models or our key programming languages; we do expect that you have the aptitude to develop these skills and knowledge, and that you are excited about revealing human activity across the global ocean using these tools. If you don’t think you check all the boxes, but believe you have unique skills that make you a great fit for the role, we want to hear from you!

Additional Information

Reporting to: Senior Data Scientist / Senior Data Science Manager

Manages: NA

Location: Remote - we welcome candidates based in any country

Term: Permanent position

FT/PT: Full-time

Recruiting process

A cover letter along with a CV will be requested to see how your experience and interest connect to the position. We expect the cover letter to explain details on how your skills, interests, and aspirations align with the role. If selected for consideration, the hiring process for this position will include a formal 45 minute interview with 2-3 staff followed by a 30 minute administrative screening by a Human Resources manager. Candidates advancing beyond this round will be asked to take a technical assessment. Lastly, an informal 30 minute call with 3-4 members of the Research and Innovation team will be held with finalists.

Please apply by January 26, 2024

Working Hours: Global Fishing Watch supports flexible working, so the pattern of hours may vary according to operational and personal needs. The position will be part of a global team spanning many different time zones and so the candidate should be able to accommodate semi-regular early/late meetings to be able to work effectively. Weekend work may be required on occasion. The post holder may be required to undertake regional and international travel. No overtime is payable.

Compensation: A compensation range for this position is US$ 90,000-$110,000 for US-based employees - For applicants located outside of the US, the pay range will be adjusted to the country of hire. Compensation is commensurate with experience and will vary depending on the hired candidate’s country of residence, in accordance with local laws and regulations. GFW offers pension/retirement, health and other benefits commensurate with similar level GFW employees in the country of employment. The position may be a GFW employee or consultant, depending on the country of residence  

Equal opportunities: Global Fishing Watch is an equal opportunities employer. Global Fishing Watch is committed to promoting diversity and inclusion within our organization and in the greater ocean management and conservation community. We believe that diverse backgrounds, skills, knowledge, and viewpoints make us a stronger organization. Bringing together professionals who possess broad experiences and a spectrum of perspectives will enable us to reach our goal of improved ocean governance faster. We hire and promote qualified professionals without regard to actual or perceived race, color, religion or belief, sex, sexual orientation, gender identity, marital, or parental status, national origin, age, physical or mental disability or medical condition, or any other characteristic protected by applicable law. Our organizational goals match the urgent challenges facing our global ocean, and our mission is designed to help secure a healthy ocean for all. We are committed to building a workforce that is representative of humanity’s diversity, by providing an inclusive and welcoming environment for all employees of Global Fishing Watch and for our partners, vendors, suppliers, and contractors.

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