Doktar is an Agritech company with a purpose of improving food systems through intensive use of data and data driven decisions. To fulfill its purpose, Doktar delivers a palette of digital services to the entire agricultural value chain. Doktar is positioned as a one-stop shop for digital agriculture solutions, which requires us to develop and deliver a set of services based on emerging technologies, such as remote sensing, internet of things, machine learning and artificial intelligence.
We are looking for a Machine Learning Engineer who is passionate about the machine learning, computer vision, and big data to improve the agricultural environment, support today’s farmers and lead sustainable data-driven agri-food ecosystem.
Roles & Responsibilities
- Drive the end-to-end execution of the ML/AI development, from understanding requirements, data discovery, model development and evaluation, to implementation of a full production pipeline for both batch and stream-based deployment.
- Develop production-grade machine learning code, from models to features and pipelines, allowing for scalability, realtime, monitoring and retraining.
- Monitor product health, performance and business impact and act accordingly when requirements are not met.
- Develop the strategy and research plan for machine intelligence on a product family by designing innovative ML/AI models, algorithms, and approaches that deliver both short-term commercial impact and longer-term differentiated business value and customer experiences.
- Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of ML/AI disciplines and related fields. Coach others through evidence and clear communication, explaining advanced technical concepts in simpler terms.
- Continuously evolve your craft by keeping up to date with the latest developments in ML/AI and related technologies, introducing them to the machine learning community and promoting their application in areas where they can generate impact.
- Document and share the findings, and generalize these technologies into reusable frameworks.
Key Skills & Qualifications
- Strong relevant work or academic experience involved in the development and application of Machine Learning.
- Strong experience in one or more programming languages such as Python, R, Java, C++.
- Strong experience working with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Strong experience working with cloud computing platforms such as AWS, Azure or Google Cloud.
- Knowledge of software development best practices, such as testing, version control, and continuous integration/deployment.
- Ability to write production-quality code.
- Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
- Strong problem-solving and critical thinking skills.
- Strong communication and collaboration skills.
What We Offer
- An interesting and highly autonomous job in a young and interdisciplinary team;
- Participation in national & global-scale projects;
- State-of-the-art technical facilities (software and communication tools);
- Professional development opportunities;
- Hybrid work and flexible working hours;
- Company shares options;
- Private health insurance covering family members under 22 years;
- Monthly lunch fee (vouchers);
- Performance-based yearly bonuses.