Senior Backend Engineer

Description

We are seeking a highly skilled Engineer to join our innovative team focused on developing and optimizing next-generation engines.

In this role, you will be responsible for designing, enhancing, and scaling bioinformatics pipelines using state-of-the-art AI models to deliver high-quality mathematical models of human biology.

The ideal candidate will possess a strong background in backend and data engineering.

Responsibilities

• Lead the design of scalable and maintainable software architectures for AI systems and data pipelines.
• Take a major part in leading the designing, development, and optimization of high-scale pipelines and data infrastructure.
• Make critical technical decisions regarding tools, frameworks, and methodologies to be used in projects.
• Develop technical roadmaps and strategies to align with business objectives and drive technological advancements.
• Work closely with data scientists, machine learning engineers, bioinformatics developers, and product managers to integrate algorithms into end-to-end AI solutions and workflows.
• Provide guidance, mentorship, and training to junior developers, ensuring high code standards and execution excellence across the team.

Requirements

• Relevant education or experience in Computer Science, Machine Learning, Mathematics, Statistics, or a relevant experience 
• 6+ years of experience as a software engineer, with at least 1-2 years in a leadership or senior technical role
• Proficiency in Python & R
• Knowledge of data processing frameworks such as pandas
• Proficiency in version control systems such as Git
• Experience with SQL and NoSQL databases
• Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for model training and deployment
• Familiarity with containerization technologies like Docker and Kubernetes
• Understanding of computational methods for large-scale data
• Experience in the development of high-data and compute-intensive systems
• Demonstrated ability to optimize algorithms for scalability and performance in large-scale data environments
• Experience working in multidisciplinary teams with data scientists, software engineers, and product managers
• Strong communication skills to effectively convey complex technical concepts to both technical and non-technical audiences
• Excellent problem-solving and communication skills

Advantages

• Knowledge of data processing frameworks such as pandas
• Experience with SQL and NoSQL databases
• Familiarity with containerization technologies like Docker and Kubernetes. 
• Understanding of computational methods for large-scale data.
• Experience with machine learning libraries and frameworks such as Pandas, Numpy, SciPy, TensorFlow, PyTorch, Keras, etc.
• Experience with R and R libs like dplyr, caret, xgboost, Bioconductor, etc
• Strong communication skills to effectively convey complex technical concepts to both technical and non-technical audiences.