Responsibilities:
- Design and develop a range of classical and deep learning algorithms for modeling complex interactions within enterprise environments.
- Create algorithms for statistical modeling of cybersecurity risks.
- Utilize datamining AI and graph analysis techniques for various challenges including modeling relevance determination and recommendation systems.
- Deliver productionquality solutions that balance complexity and efficiency.
- Participate in the engineering lifecycle at Balbix including designing ML infrastructure and data pipelines writing production code conducting code reviews and collaborating with infrastructure and reliability teams.
- Drive the architecture and utilization of opensource numerical computation libraries such as TensorFlow PyTorch and ScikitLearn.
Requirements
- Ph.D./M.S. in Computer Science or Electrical Engineering with handson software engineering experience.
- Minimum of 5 years experience in machine learning and Python programming.
- Expertise in programming fundamentals and building largescale systems.
- Knowledge of stateoftheart algorithms statistical analysis and modeling techniques.
- Strong understanding of NLP Probabilistic Graphical Models Deep Learning with graph structures and model explainability.
- Foundational knowledge of probability statistics and linear algebra.
Desired Skills:
- Ability to tackle complex problems learn quickly and persist until finding robust solutions.
- Passion for building practical and userfriendly systems.
- Collaborative mindset comfortable working across teams.
- Ownership mentality towards challenging problems.
- Excellent communication skills and documentation practices.
- Comfort with ambiguity and ability to design algorithms for evolving needs.
- Intuitive understanding of selecting appropriate models for different product requirements.
- Curiosity about the world and profession with a commitment to continuous learning.
Requirements: Ph.D./M.S. in Computer Science or Electrical Engineering with hands-on software engineering experience. Minimum of 5 years' experience in machine learning and Python programming. Expertise in programming fundamentals and building large-scale systems. Knowledge of state-of-the-art algorithms, statistical analysis, and modeling techniques. Strong understanding of NLP, Probabilistic Graphical Models, Deep Learning with graph structures, and model explainability. Foundational knowledge of probability, statistics, and linear algebra. Desired Skills: Ability to tackle complex problems, learn quickly, and persist until finding robust solutions. Passion for building practical and user-friendly systems. Collaborative mindset, comfortable working across teams. Ownership mentality towards challenging problems. Excellent communication skills and documentation practices. Comfort with ambiguity and ability to design algorithms for evolving needs. Intuitive understanding of selecting appropriate models for different product requirements. Curiosity about the world and profession, with a commitment to continuous learning.