Junior AI/ML Engineer

Job Title: Junior AI/ML Engineer

Location:** Austin TX - Hybrid

**Department:** Engineering / Data Science

**Employment Type:** Full-time

Position Overview

We are looking for a passionate and motivated Junior AI/ML Engineer to join our growing tech team. In this role, you will work closely with senior engineers and data scientists to build, optimize, and deploy machine learning models within our enterprise ecosystem.

This is an entry-level position designed for entry level candidates, bootcamp alumni, or self-taught developers with a strong foundation in coding, mathematics, and data structures who are eager to kickstart their career in Artificial Intelligence. You will receive hands-on mentorship, exposure to real-world datasets, and the opportunity to scale your skills rapidly.

Responsibilities

Data Preparation:Assist in gathering, cleaning, preprocessing, and labeling structured and unstructured data for training ML models.

Model Development:Support the team in building, training, and testing basic Machine Learning and Deep Learning models under supervision.

Pipeline Maintenance:** Assist in maintaining and improving existing data pipelines and feature engineering processes.

* **Evaluation & Testing:** Run evaluation metrics to track model performance and document experimental results.

* **Enterprise Integration:** Work alongside software engineers to help integrate ML models into production applications and core business workflows.

* **Continuous Learning:** Stay up-to-date with the latest AI/ML trends, frameworks, and research papers, actively applying new knowledge to team projects.

Required Skills & Qualifications

* **Education:** Bachelor s degree in Computer Science, Data Science, Statistics, Mathematics, Economics, or a related technical field (or equivalent practical experience/portfolio).

* **Programming:** Proficient in Python (knowledge of libraries like NumPy, Pandas, and Scikit-Learn is essential).

* **ML Foundations:** Clear understanding of core ML concepts (e.g., supervised vs. unsupervised learning, regression, classification, overfitting/underfitting).

* **Mathematics:** Solid grasp of linear algebra, calculus, probability, and statistics.

* **Tools:** Basic familiarity with Git / Version Control.

Preferred (Nice-to-Have) Qualifications

* **Insurance Technology:** Basic familiarity or exposure to Guidewire Software (e.g., InsuranceSuite, PolicyCenter, ClaimCenter, or BillingCenter) is highly advantageous.

* **Industry Domain:** Knowledge of or exposure to the Insurance Industry (e.g., understanding risk assessment, claims processing, underwriting, or actuarial concepts).

* **Cloud Platforms:** Basic knowledge of cloud computing services (AWS, Azure, or Google Cloud Platform) and how they relate to data storage, serverless computing, or model deployment.

* **Advanced Frameworks:** Familiarity with Deep Learning frameworks like PyTorch or TensorFlow.

* **Data Management:** Basic knowledge of SQL and relational databases.

* **DevOps Basics:** Exposure to containerization tools like Docker.

* **Portfolio:** Academic projects, Kaggle participation, or a GitHub portfolio demonstrating a strong interest in data science or AI/ML.

What We Offer

* **Mentorship:** Dedicated guidance from senior AI/ML practitioners to help you grow.

* **Impact:** The chance to work on real-world projects that directly impact our business.

* **Growth:** A clear career progression path from Trainee to Mid-level Engineer.