Python Developer

Senior Python Engineer (ML/AI).

We are looking for an experienced Python Engineer (ML/AI) to help transform scientific and algorithmic solutions into reliable, scalable, and production-ready software.

This role will work closely with algorithm development, bioinformatics, data science, and engineering teams to take algorithms and research prototypes and integrate them into robust production systems. The ideal candidate combines strong Python software engineering skills with experience in machine learning, bioinformatics pipelines, and/or scientific computing.

You will collaborate in an agile environment to deliver secure, performant, maintainable, and well-documented software while following established engineering practices and design standards.

Essential Duties and Responsibilities.

• Develop, enhance, and maintain high-quality software applications and services using Python .

• Partner with algorithm, bioinformatics, and data science teams to convert research algorithms and prototypes into production-ready solutions.

• Contribute to new initiatives involving AI/ML technologies.

• Support the full ML lifecycle, including experimentation, algorithm validation, deployment, inference, monitoring, and ongoing maintenance.

• Build and maintain reliable data pipelines, ensuring data quality, traceability, and integrity throughout processing workflows.

• Implement ML engineering and MLOps practices, including model versioning, automated testing, CI/CD, deployment, monitoring, and reproducibility.

• Evaluate and integrate appropriate AI/ML technologies, including traditional ML models, computer vision models, Vision Transformers, LLMs, RAG architectures, and agentic capabilities when applicable.

• Optimize AI/ML solutions for accuracy, latency, scalability, reliability, and operational cost.

• Create and maintain technical and regulatory documentation supporting software, algorithms, workflows, and production systems.

• Ensure software and pipeline implementations support traceability, reproducibility, verification, and validation requirements appropriate for regulated environments.

• Implement software engineering best practices, including software design, peer code reviews, unit testing, integration testing, and continuous integration.

• Apply knowledge of system architecture, software design, and cloud computing to develop scalable and maintainable solutions.

• Design and implement appropriate system security and data protection practices. .

• Develop and maintain cloud-native solutions, particularly within AWS .

• Leverage AI-assisted development tools to improve engineering productivity, software quality, and development workflows.

• Troubleshoot and resolve complex technical issues across applications, pipelines, models, and cloud infrastructure.

• Collaborate closely with software engineers, bioinformaticians, data scientists, scientists, quality engineers, and other cross-functional stakeholders.

• Document requirements, technical specifications, architectures, workflows, and system designs.

• Create diagrams, flowcharts, and other technical documentation as needed.

• Provide technical guidance and support to other engineers when appropriate.

• Clearly articulate technical designs, trade-offs, risks, and recommendations to both technical and non-technical stakeholders.

• Stay current with emerging technologies and best practices in Python, bioinformatics, AI/ML, computer vision, MLOps, and cloud engineering.

• Uphold company values through accountability, innovation, integrity, quality, and teamwork.

Minimum Qualifications.

• Bachelor's degree in Computer Science, Software Engineering, Bioinformatics, Computational Biology, or a related field, or equivalent professional experience. .

• 5+ years of relevant software engineering experience.

• Strong hands-on experience designing, developing, testing, and maintaining production-quality software using Python.

• Strong understanding of software engineering fundamentals, including object-oriented design, software architecture, design patterns, version control, testing, and CI/CD.

• Experience writing unit and integration tests and maintaining appropriate automated test coverage.

• Experience developing applications or data-processing systems in AWS, including cloud-native or serverless technologies such as Lambda.

• Experience taking algorithms, scientific prototypes, or analytical workflows and converting them into reliable production software.

• Experience designing or maintaining data-intensive, scientific, or bioinformatics pipelines.

• Strong technical understanding of the machine-learning lifecycle, including model training, evaluation, validation, deployment, inference, and monitoring.

• Ability to collaborate effectively with data scientists, bioinformaticians, or algorithm developers and translate experimental implementations into production-quality systems.

• Strong problem-solving and debugging skills.

• Strong written and verbal communication skills.

• Ability to work effectively within cross-functional and agile teams.

Nice-to-Have Qualifications.

• Experience working in biotechnology, healthcare, diagnostics, or life sciences.

• Experience working in a regulated environment, preferably GMP, ISO, clinical, or diagnostic development environments.

• Experience creating or contributing to regulatory, verification, validation, or design-control documentation.

• Familiarity with Laboratory Information Management Systems (LIMS).

• Knowledge of clinical or diagnostic test development processes.