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# Automation Engineer - Scientific Data, AI/ML Pipelines & Integration Dev

- **Company:** Zifo Technologies Inc.
- **Location:** Indianapolis, IN, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Code Review, Data Cleansing, Data Integrity, Extract Transform Load (ETL), Relational Databases, Database Queries, Software Debugging, Django Web Framework, Amazon DynamoDB, Github, Identity and Access Management, Python (Programming Language), Laboratory Information Management Systems, PostgreSQL, Machine Learning, MongoDB, MySQL, NoSQL, NumPy, Oracle (Applications), Performance Tuning, Scrum Methodology, Systems Development Life Cycle, Mockito, Tensorflow, Software Deployment, SQL Databases, Systems Integration, Data Logging, Enterprise Software Applications, Test-Driven Development (TDD), Feature Engineering, Data Ingestion, Pytorch, Flask (Web Framework), Delivery Pipeline, State Machines, Backend, Fastapi, Pandas, Amazon Relational Database Service, Pytest, Containerization, Gitlab-ci, Scikit Learn, Information Technology, Atlassian Tools, Data Management, Functional Programming, Restful APIs, Data Pipelines, GXP, Docker, Jenkins, Microservices
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/automation-engineer-scientific-data-ai-ml-pipelines-integration-dev-zifo-8044144

## About the Role

Zifo is seeking a passionate Software Developer who can work at the intersection of science, data, and technology. The role requires strong expertise in Benchling, Python, SQL/NoSQL, AWS and FastAPI, along with the ability to work directly with scientists performing assay-based experiments. The successful candidate will translate experimental workflows into robust data components, scientific system integrations, AI-enabled insights, and next-generation data pipelines, * Bachelor's or master's degree in computer science, Engineering, Life Sciences with 3-8 years of hands-on experience in Python development with FastAPI

 * Proficiency in SQL, including schema design, complex queries, and performance optimization
 * Relational databases such as PostgreSQL, MySQL, Oracle, AWS RDS/Aurora, NoSQL databases such as DynamoDB, MongoDB, or equivalent
 * Experience with scientific data and laboratory informatics, including familiarity with Benchling or similar scientific data platforms ELN like Benchling, LIMS, ELN, SDMS, CDS,, within the life sciences or pharmaceutical industry. (Preferred)
 * AWS experience, including S3, EC2, Lambda, Step Functions, RDS / Aurora, IAM, monitoring, and logging
 * Proficiency with Git-based collaborative development, including branch management, pull requests, code reviews, and integration with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, AWS CodePipeline) to ensure reliable and traceable software delivery
 * Hands-on experience with Test-Driven Development and Python testing frameworks such as pytest, unittest, and mocking libraries
 * Working knowledge of AI/ML concepts, including data preparation, feature engineering, model integration, and inference workflows
 * Exposure to the data and ML libraries such as pandas, NumPy, and scikit-learn (exposure to TensorFlow or PyTorch is a plus)
 * Ability to design data models aligned to scientific and assay workflows & integrating scientific or enterprise systems and working directly with scientists or lab users
 * Knowledge of containerization (Docker) and modern deployment best practices
 * Familiarity with Agile/Scrum & SDLC development methodologies & Solid understanding of REST APIs, microservices, and integration patterns
 * Strong communication, stakeholder engagement, and cross-team coordination skills

Additional Preferences

 * Willingness to travel/ relocate based on project or business needs
 * Ability to work in a fast-paced, client-focused environment
 * Comfortable managing cross-team coordination and dependency management, particularly across globally distributed teams and user groups

## Description

* Collaborate with scientists, assay teams, and lab operations to capture end-to-end assay and experimental workflows, from sample onboarding and execution through data ingestion, validation, and downstream analytics
 * Translate scientific and operational requirements into well-defined functional, technical, and data requirements for laboratory platforms, system integrations, and next-generation data pipelines
 * Design, develop, and maintain Python-based backend services, APIs, microservices, and data pipelines on AWS using FastAPI and supporting frameworks such as Flask or Django, including integrations with scientific systems such as Benchling, Signals, LIMS, ELN, CDS, and SDMS.
 * Design and optimize SQL and NoSQL data models and build ETL/ELT and next-generation data pipelines to support structured, semi-structured, and high-volume scientific data, analytics, and AI/ML workloads, including dataset preparation, feature engineering, and model integration into pipelines and applications.
 * Implement and maintain CI/CD pipelines for automated build, testing and deployment
 * Ensure solutions meet performance, data integrity, security, and regulatory compliance requirements (e.g., GxP, 21 CFR Part 11)
 * Perform code reviews, debugging, and performance optimization
 * Coordinate across cross-functional and geographically distributed teams, managing dependencies and ensuring delivery alignment
 * Create ready to deliver technical documentation and track deliverables using JIRA and Confluence


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