AI/ML Software Engineer(NLP)

• Separate core modeling workflows from the Streamlit application into a reusable Python package.
• Improve code structure, testing, and CI/CD reliability in alignment with department standards.
• Enable programmatic (non-UI) access to FLIK capabilities.
• Develop architecture documentation and contributor guidance, including support for AI-assisted development.
• Reduce operational risk by improving testability, reliability, and CI/CD practices.
• Make FLIK maintainable by introducing clear architecture, documentation, and coding conventions.
• Enable reuse by decoupling modeling workflows from the Streamlit UI and supporting non-UI access.
• This allows the data science team to focus on evolving methods and delivering value to users, while ensuring the underlying system is robust, extensible, and aligned with department standards., * Participate in OP monthly team meetings and participate in team-building efforts.
• Contribute to OP technical discussions, peer reviews, etc.
• Contribute content and collaborate via the OP-Wiki/Knowledge Base.
• Provide status reports to OP Account Management as requested.

• Python software architecture & refactoring: Experience separating reusable domain logic from UI/framework layers in complex applications, especially in data science contexts.
• Testing, CI/CD, and operational hardening: Strong experience with pytest, integration testing, and CI/CD pipelines (GitLab, Docker); ability to improve reliability in existing systems.
• Python packaging and interface design: Experience designing installable.
• Python packages and defining clear programmatic interfaces (e.g., scriptable, API-friendly, or tool-compatible access) Streamlit at production scale: Experience working with Streamlit applications.
• (multi-page apps, session state, callbacks), With a focus on maintainability and testing.
• Developer experience for humans and AI-assisted tools: Ability to write clear documentation, architecture guidance, and coding conventions that enable both developers and AI coding assistants to work effectively in the codebase.
• Are there any specific programs or software with which this candidate needs to be familiar, or that would be a bonus if they had?, * Languages: Python, R (bonus).
• Core application stack: Streamlit (multi-page app, session state, callbacks); pytest, Git + GitLab (MRs, CI pipelines), Docker.
• Heavily used Python libraries: pandas, NumPy, scikit-learn, spaCy, NLTK, Gensim, Transformers / ONNX Runtime / Optimum, LangChain, LangGraph, LangChain OpenAI, Plotly, matplotlib, pyLDAvis, Pydantic / pydandic-settings (comfort reading and integrating these libraries is sufficient; our data science team owns the modeling and NLP methodology).
• Dev tooling: pre-commit, Black, Ruff, mypy, docformatter, Sphinx.
• Python packaging; streamlit ecosystem; infrastructure & deployment; AI-assisted development; documentation & quality(bonus).

• 401(k).
• Dental Insurance.
• Health insurance.
• Vision insurance.
• We are an equal-opportunity employer and value diversity, equality, inclusion, and respect for people.
• The salary will be determined based on several factors, including, but not limited to, location, relevant education, qualifications, experience, technical skills, and business needs.

At OP, we help you harness the power of technology for maximum impact. A technology consulting and solutions company, we offer advisory and managed services, innovative platforms, and staffing solutions across a wide range of fields including AI, cyber security, enterprise architecture, and beyond. For nearly two decades, we’ve been challenging the status quo of the consulting industry, serving up fresh, ingenious thinking through a radically lean structure. Together, this strategy delivers unprecedented performance at an unparalleled pace for faster results that propel your business forward.