Algorithm Engineer
1 tydzień temu
Fetcherr experts in deep learning, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.
We are looking for an
Algorithm Engineer
to join our team and help design, develop, and optimize data-driven algorithms for complex decision-making problems. The ideal candidate has strong analytical skills, a deep understanding of algorithmic development, and experience working with large datasets and optimization techniques.
Responsibilities
:
- Design and develop the core algorithms that drive Fetcherr's optimization and decision-making engine
- Work with large-scale datasets, developing efficient data structures and processing techniques
- Implement and optimize mathematical models that power the product's core decision-making logic which use machine learning–based forecasts as inputs
- Collaborate with data scientists and engineers to integrate algorithms into production systems
- Ensure performance, scalability, and robustness of deployed algorithms
Requirements:
You'll be a great fit if you have...
- 3+ years of experience in algorithm development using Python
- Strong background in data structures, algorithms, and computational complexity
- Hands-on experience with optimization techniques, graph algorithms, or statistical modeling
- Fluent with Python and libraries such as NumPy, SciPy, Pandas
- Proficiency with SQL and NoSQL databases
- Strong software engineering practices, including version control and testing
- A willingness to continuously learn and improve
- A B.Sc. or Master's degree in Computer Science, Mathematics, Engineering, or a related field
Nice to have:
- Experience with mathematical optimization (e.g., linear programming, convex optimization)
- Exposure to MLOps and cloud-based infrastructure (e.g., Kubernetes, Airflow, Dagster, Docker)
- If you're passionate about solving complex algorithmic problems and want to work in a
- fast-paced, AI-driven environment, we'd love to hear from you
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