Senior Python (ML/AI) Engineer

ITJ; United States; Remote; MXN 600,000 - 1,000,000; Full time

Job summary

ITJ in Mexico is seeking an experienced Python Engineer (ML/AI) to turn research algorithms into robust, scalable production software. You will work with algorithm development, bioinformatics, data science, and engineering teams to deliver secure and maintainable systems.

The role emphasizes cloud-native solutions in AWS, ML workflow automation, and rigorous software engineering practices to ensure reliability and traceability across production pipelines.

Qualifications

• 5+ years of software engineering experience in Python.
• Strong Python software engineering fundamentals and production-quality skills.
• Experience AWS cloud-native or serverless (Lambda) is required.
• Experience converting research prototypes into production software.
• Understanding ML lifecycle: training, evaluation, deployment, monitoring.

Responsibilities

• Develop and maintain production-grade Python applications and services.
• Collaborate with algorithm, bioinformatics, and data science teams to productionize research.
• Contribute to AI/ML initiatives and MLOps practices.
• Support ML lifecycle from experimentation to monitoring and maintenance.
• Build data pipelines ensuring quality, traceability, and integrity.

Skills

Python

AWS

ML lifecycle

CI/CD

Testing

Data pipelines

Tools

Nextflow

Snakemake

PyTorch

TensorFlow

LIMS

Job description

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

• 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.

Preferred / Nice-to-Have Qualifications

• Experience developing bioinformatics pipelines, particularly workflows related to NGS.
• Experience with Nextflow, Snakemake, or similar scientific workflow orchestration technologies.
• Experience with computer vision, medical image analysis, image processing, or Vision Transformers.
• Experience developing or deploying machine-learning solutions using frameworks such as PyTorch, TensorFlow, or similar technologies.
• Experience implementing production MLOps solutions, including experiment tracking, model registries, automated deployment, monitoring, and model lifecycle management.
• Familiarity with genomic data formats, sequencing workflows, variant analysis, or other computational biology concepts.
• Experience working with large scientific datasets and distributed or high-performance computing workflows.
• Familiarity with LLMs, RAG architectures, and AI agents.
• 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.