We are looking for a highly skilled Technical Architect, Backend to drive the design, development, and implementation of scalable and efficient backend architectures. The ideal candidate will have strong expertise in machine learning, deep learning, data analysis, and backend system architecture. You will play a key role in collaborating with engineers, IT teams, and other stakeholders to create solutions that meet both technical and business requirements.
Key Responsibilities:
Data Analysis G Visualization: Collect, analyze, and interpret data, develop visualizations, and draw inferences from experimental Present findings to biologists and other stakeholders in an understandable manner.
Algorithm G Model Development: Improve and implement analysis algorithms and machine learning models such as k-NN, artificial neural networks, and linear/logistic regression.
Machine Learning G Deep Learning: Engage heavily in machine learning and deep learning, including the development and fine-tuning of models for different use cases.
Collaboration G Communication: Communicate with engineers, IT teams, and other stakeholders, sharing complex technical concepts both verbally and visually to ensure understanding by non-technical audiences.
Leadership G Mentorship: Provide technical leadership, guiding the team in the application of algorithms and machine learning techniques to solve complex problems.
Required Skills:
Machine Learning G Data Analysis: Experience in developing and deploying machine learning models (e.g., k-NN, neural networks, regression) and using data querying languages and statistical software.
Programming G Algorithm Development: Proficient in writing algorithms, with a deep understanding of when and how to apply them effectively.
Mathematical G Statistical Expertise: Strong understanding of statistics, multivariable calculus, linear algebra, and their application to machine learning and backend systems.
Data Visualization: Expertise in using data visualization tools to communicate complex data-driven insights.
Communication Skills: Excellent ability to articulate complex technical concepts to non-technical stakeholders and present findings in a visually digestible format.
Technical Knowledge: Deep understanding of computer science, software architecture principles, and backend development practices.
Preferred (Nice-to-Have) Skills:
Life Sciences/Biotechnology: Experience or coursework in life sciences or biotechnology would be an advantage.
Deep Learning Frameworks: Familiarity with deep learning frameworks like TensorFlow or PyTorch, particularly for analyzing images or time-series data.
Cloud Platforms: Knowledge of cloud computing platforms (AWS, Azure, GCP) and experience in leveraging them for machine learning and backend services.
ualifications:
Education: Bachelor s degree in Engineering, Computer Science, or a related field.
Experience: 2+ years of experience in machine learning, backend systems, and data analysis.
Why Join Us
Competitive Compensation: Attractive salary with performance-based incentives.
Innovative Environment: Join a collaborative and innovative team, working on cutting-edge technologies in machine learning and backend systems.
Professional Growth: Opportunities to expand your skills in backend architecture, machine learning, and data science.
Work-Life Balance: Flexible working hours and a culture that values both personal and professional well-being.