Data Science ML/GenAI Engineer

RemotemidPosted Aug 17, 2026

PythonDatabricksLLMsPyTorchscikit-learnpandasMLflow+19 more

About this role

Join Irth Solutions to develop production-ready AI and ML solutions for damage prevention and asset integrity. You'll work across NLP/LLM experimentation, data pipelines, and software engineering to move initiatives from prototype to production.

Must have

3-5 years experience in data science, machine learning, or ML engineering with production-quality code

Master's degree or equivalent in data science, machine learning, computer science, statistics, or related field

Hands-on experience developing NLP and/or LLM-based solutions including RAG and embeddings

Strong proficiency in Python with pandas, scikit-learn, PyTorch, and other ML libraries

Strong understanding of object-oriented programming, clean code, and software design principles

Strong data analysis skills with exploratory data analysis, hypothesis testing, and statistical modeling

Hands-on experience with Databricks or comparable data/analytics platform

Solid understanding of machine learning lifecycle including training, evaluation, deployment, and monitoring

Experience designing and developing REST APIs to expose data, models, or analytical results

Strong written and verbal communication skills for cross-team collaboration

Technologies

PythonSparkTypeScriptGitRESTTestingMachine learningCloudOOPDesign PatternsClean CodepandasSaaSscikit-learnPyTorchData scienceNLPDatabricksMLflowCI/CDLLMsPrompt engineeringNode.jsGitHub ActionsStatisticsRAG

Responsibilities

Design, prototype, and evaluate LLM/NLP solutions for text classification, entity extraction, semantic search, and summarization

Translate successful prototypes into production-ready solutions using clean, modular, maintainable, well-tested code

Apply sound object-oriented design and software engineering practices when developing and restructuring solutions

Analyze existing codebases, data pipelines, and applications to determine preservation, improvement, consolidation, or redesign

Explore, prepare, transform, and analyze data independently using Databricks to support ML models and pipelines

Collaborate with data engineering and application development teams to integrate Databricks, pipelines, models, and services

Participate in technical discussions and architectural decisions providing recommendations for maintainable solutions

Help establish development practices improving reliability, scalability, testing, and maintainability of data science solutions

Work collaboratively with engineering, data, and leadership teams to translate business requirements into technical solutions

Benefits

Health insuranceDental insuranceVision insuranceRetirement benefits with matchPaid vacationFlexible hoursCompetitive salaryRemote work

Amenities

Work-from-home opportunities available depending on role and business needsOn-call compensation for eligible shiftsCompany-paid holidays throughout the year