Machine Learning Engineer
Athens, Greece
πριν από 2 μέρες
source : Just Join IT

Software Engineering (regular)

About Appsilon

Appsilon is an ambitious and fast-growing software house and consultancy specializing in decision support systems and machine learning with Fortune 500 clients across the globe.

We are a unique company driven by a mission to improve our society and environment. Some examples of our #data4good work include contributing to wildlife preservation in the National Parks of Gabon, building COVID-19 dashboards, and improving data science tools for Doctors Without Borders.

In the machine learning space we specialize in computer vision, applying it in cases making impact on biodiversity and researching new approaches.

We are also a global leader in R and Shiny , which are used by companies of all sizes to build analytical applications. When companies run into difficult problems or want to initiate large-scale enterprise projects, they come to Appsilon.

Before you apply, please read our code of conduct .

Every few months we start completely new projects and dive into a completely new world. One day we identify species of monkeys lurking behind trees of a rainforest, another day we analyze satellite images to help mitigate natural disasters, and then dive into the arctic ocean, helping researchers understand the changes in those ecosystems.

Our projects are not only an opportunity to test our skills in difficult statistical, algorithmic, and technological problems but also an opportunity to learn about different research fields and, most importantly, contribute to their advancement.

Some examples of our past projects :

  • Open source wildlife detection app , built for usage in remote areas
  • Analysis of damage after natural disasters based on satellite images : https : / / / apps / building damage assessment
  • We took 5 / 811 place in the Hakuna Ma-data competition
  • A research paper applying machine learning in ecological modelling
  • Your Role as a Machine Learning Engineer

    Regular duties will include :

    Preparing data

  • Collecting, curating, possibly preprocessing a dataset
  • EDA - exploratory data analysis

  • Understanding and visualizing statistical properties and peculiarities of the dataset
  • Modelling

  • Running and monitoring model’s training
  • Investigating the model’s performance, identifying strong and weak points
  • Pipeline setup and improvements

  • Making sure the process above is modular and reproducible
  • Handling meetings with the client / partner

  • Sharing results, challenging assumptions, understanding the role of ML in their workflow
  • Helpful skills and experience

    Hard skills

  • Great Software Engineering background
  • Extensive Python knowledge
  • Experience with PyTorch or Tensorflow
  • Experience in data wrangling
  • Experience with machine learning pipelines and experiment reproducibility
  • Soft Skills

  • Trained analytical thinker
  • Able to switch between hacker mentality of getting things to work and organized engineer adhering to basic principles when refactoring or building key pipeline elements
  • Able to abstract from technical issues and communicate also on high level
  • At least B2 level of English
  • What’s in it for you?

  • Salary 10000 - 16000 PLN + VAT on B2B contract
  • 26 days of paid holidays + an equivalent of public holidays in Poland, est. 11 days in 2021
  • 5% of salary in Professional Development Budget to spend on activities that help you grow
  • 33 days (paid 80%) per year on B2B when on a sick leave
  • Remote work with flexible working hours adjusted to your time zone and family life.
  • 4 paid days per year to be used for training / conferences, events, or workshops for your professional development
  • Private health care insurance (in Poland) (Polmed)
  • Life insurance
  • FitProfit or FitSport membership card (in Poland)
  • AskHenry a personal assistant works great in large Polish cities, elsewhere limited to online support
  • Projects that have a real impact on the world. More on https : / / / data-for-good /
  • Technologies and tools you will be using

  • All sorts of Pythonic tools for
  • Data processing - pandas, numpy, Pillow, opencv,
  • Data visualisation - matplotlib, seaborn, plotly,
  • Modelling - PyTorch (and, TensorFlow (and Keras), scipy,
  • Experiment tracking - Weights&Biases, Neptune, Domino, Tensorboard,
  • Dashboards - rather limited, but still maybe sometimes - streamlit, django, starlette, ...
  • Occasionally R world
  • Mostly to interface with Shiny dashboards
  • Possibly if data source / preprocessing was implemented in R by a client
  • Code tools (GitHub / GitLab, your favourite IDE, sometimes RStudio)
  • General tools (bash / shell)
  • Internal tools (Slack, Outline, Clickup, G Suite)
  • What can you expect during the recruitment process?

  • Screening call with Talent Manager
  • Home assignment
  • Interview with the ML Team
  • Conversation with the CTO
  • Αναφορά αυτής της εργασίας

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