Algorithm Engineer

About

Algorithm Engineer focus on developing, optimizing and productionizing computational methods for personalized healthcare, specifically DNA sequencing, digital pathology and image analysis.

Key Responsibilities

Algorithm Development & Optimization

• Design, implement and optimize AI/machine learning algorithms (e.g., Transformers, CNNs, Hidden Markov Models) for analyzing raw nanopore signal data and DNA sequencing (basecalling).

Productionization (MLOps)

• Convert research code (Python/PyTorch/TensorFlow) into highly efficient, production-ready and scalable C++ or CUDA code for GPU cluster efficiency

Pipeline Development

• Architect distributed computing workflows and data pipelines using tools like Nextflow, Airflow and Docker/Singularity for high-performance computing (HPC) environments

Data Analysis & Modeling

• Apply computational methods to NGS datasets (genomics, transcriptomics) to identify biomarkers and develop diagnostic, predictive and classification models.

Verification & Validation

• Develop automated testing frameworks for digital pathology and imaging algorithms to ensure technical accuracy and performance.

Education

Typically a Master’s or PhD in Bioinformatics, Computer Science, Computational Biology, Electrical Engineering or a related field.

Technical Skills

Languages

• Strong proficiency in Python (including libraries like PyTorch/TensorFlow) and C++/CUDA.

Platforms/Tools

• Experience with Linux, Docker, Git and HPC workload managers like SLURM.

Domain Expertise

• Deep knowledge of algorithms for DNA analysis (e.g., dynamic programming, Hidden Markov Models) or digital pathology/image processing.

Experience

• 5+ years of industrial experience in software development, algorithm R&D or productionizing ML models.

Key Focus Areas

Digital Pathology

• Building image processing algorithms for disease diagnostics.