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Machine Learning Specialist

EarthCare.ai

EarthCare.ai

Software Engineering
Central Macedonia, Greece
Posted on Feb 5, 2025

Ever wanted to work in a globally known startup? A startup making a real positive impact on the world, and at the same time aiming to make millions? Say hi to EarthCare.ai!

You may have heard of us as AirCare (МојВоздух) and our 2 founders Gorjan Jovanovski & Dragan Gelevski. From our famous mobile app, we’re now developing EarthCare.ai - a climate platform that helps businesses minimize risk from climate hazards and optimize their processes.

EarthCare.ai is a B2B weather & climate intelligence platform, and it’s revolutionizing how businesses access and understand the data about the world around them. We source weather data from satellites, radars, IoT devices and agencies, analyze all of them to find patterns and trends, as well as run them via our own AI models to improve forecasting and hazard detection - saving clients time, money and de-risking their assets! We already work with some of Europe's largest energy companies.

As a Techstars backed company (world’s largest pre-seed startup accelerator), we just closed our pre-seed round with the support of investors & strategic partners, and already are working with our first clients. Now, our team is expanding, and we’re looking for superstars to join the next Macedonian 🦄 unicorn startup (a unicorn startup is one valued at over $1B)!

📍 Responsibilities

  • Develop and set up machine learning pipelines from data sourcing to deployment
  • Transform, label, and combine datasets for model training
  • Build environmental and climate ML models for forecasting and insights
  • Integrate with commercial and established machine learning models
  • Analyze and interpret complex climate data to extract actionable insights
  • Collaborate with the development team to implement proprietary models
  • Contribute to the design and development of new data products and features
  • Participate in decision-making processes and contribute to product advancements

📍Requirements

  • Minimum 3 years of experience in data science and machine learning
  • Strong proficiency in data analysis tools and programming languages ( Python )
  • Experience with machine learning frameworks and cloud-based ML services
  • Knowledge of data sourcing, transformation, and management
  • Excellent problem-solving skills and attention to detail
  • Strong communication skills and proficiency in English
  • Ability to work on-site at our office (for Local hires)
  • Passionate about applying AI to solve real-world environmental challenges

📍Nice to have

  • Experience with earth observation data and climate modelling
  • Experience using non-relational databases such as MongoDB
  • Experience operating commercial machine learning models like Microsoft or Google

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What we expect from every candidate:

  • 🏆 10x engineer - hungry to tackle challenges with minimal hand-holding
  • ☝️ Proactive - always being on the lookout for better solutions & practices
  • 📍 Goal oriented - aim to set and achieve the highest result for our objectives
  • 👫 Team player - we work together on all problems, and love to hear your opinion
  • 🗣️ Open communicator - constantly talking with them team on your status and progress
  • 🚀 Startup mentality - we’re moving fast, pivoting and changing as we learn, and we need you to be able to very quickly adapt (no comfort zones except our gaming room)
  • 🤓 Ready to learn - you’ll come across a lot of new tech and areas in your job, and you should be ready to quickly get the basics to start running

What we provide for every candidate:

  • 🕰️ Flexible working hours & possibility to work from home when needed
  • 🤧 Unlimited sick days (including menstrual days)
  • 📈 Stock options, grow together with the company’s success
  • 💻 IT gear and all tech stuff needed to work
  • 🎤 Conference visits, client visits & team trips
  • 🙌 Working with founders which employ the servant leadership management style (not the typical Macedonian “boss”)
  • 🪁 Play a pivotal role in shaping our products from the ground up, contributing directly to its development and architecture rather than merely performing routine tasks or fixes