Algorithms Researcher

The position:

We are looking for a creative and experienced Algorithm Researcher to join our growing R&D department. The position aims to explore and implement novel solutions for the complex, multidisciplinary challenges at the core of our ground-breaking technology. These solutions will be based, among other fields, on big data analysis, statistical modeling, machine learning, signal processing, and computational geometry.

A day in the life:

• Engage in cutting-edge research to address real-world problems for which no “off the shelf” solutions exist. Innovatively harness ideas from algorithmic literature – both classics and state-of-the-art advances
• Cooperate with fellow researchers specializing in an array of different disciplines
• Work side-by-side with engineering teams, planning how to integrate your solution into the system’s architecture
• Implement your ideas with production-grade code
• Have complete ownership of system components serving in production across all of Trigo’s sites
• Analyze varied realistic data from stores retrofitted with Trigo’s system
• See the bigger picture; take the system as a whole into account while designing algorithmic solutions

You bring to the table:

• MSc. in Computer Science \ Electrical Engineering \ Mathematics \ Physics \ similar field
• A mission-oriented critical thinker with strong problem-solving abilities
• A team player by nature
• At least 2 years of industry experience as an algorithms researcher; preferably experienced the full development cycle of machine learning models
• Sound theoretical understanding of classical machine learning
• Strong technical abilities in object-oriented programming, preferably in Python
• Proficiency with Python’s scientific computing stack: NumPy, SciPy, Scikit-Learn, and Pandas
• Basic SQL skills

Nice to have:

• Acquaintance with deep learning theory, techniques, and frameworks (preferably PyTorch)
• Field-specific background in time-series analysis, online learning, sensor fusion, or Bayesian inference
• Experience in deep-learning based solutions, preferably computer-vision problems