AI/ML Engineer

Company
: Confidential

Location
: Austin, TX (On‑site or Hybrid)

Employment Type
: Full-Time

Job Summary:

A technology organization in Austin is seeking an Entry-Level AI/ML Engineer with a U.S.-completed Master’s degree. This role is designed for strong technical graduates who want to work on real-world machine learning applications, data engineering pipelines, and emerging AI solutions. This position offers direct exposure to production-oriented ML systems, infrastructure, and model experimentation.

**Key Responsibilities

Machine Learning & Modeling**

• Assist in training, evaluating, and tuning supervised and unsupervised ML models.
• Develop ML experiments using Python, Scikit-learn, PyTorch, TensorFlow, or similar frameworks.
• Conduct hyperparameter optimization using grid search, random search, or early stopping methods.
• Implement baseline models and compare against advanced architectures.
• Participate in building feature engineering pipelines and transformation logic.

Data Engineering & Analysis

• Clean, preprocess, and validate structured and unstructured datasets.
• Perform exploratory data analysis to identify patterns, correlations, and anomalies.
• Implement data augmentation strategies for small datasets.
• Support labeling workflows and metadata management.
• Write Python scripts to automate data extraction and transformation tasks.

LLM & NLP Support

• Assist in testing LLM-based workflows for internal tools or automation.
• Implement prompt templates and evaluate output quality.
• Conduct model benchmarking and performance comparisons.
• Assist in creating evaluation datasets for NLP tasks.

Pipeline Development & Integration

• Contribute to building end-to-end ML workflows and reproducible pipelines.
• Implement logging, experiment tracking, and version control practices.
• Assist with deploying models to testing or staging environments.
• Work with engineers to debug and optimize inference performance.
• Support integration of models with APIs or internal platforms.

Technical Documentation & Reporting

• Document model assumptions, methodologies, and parameter configurations.
• Create clear experiment logs and structured reports.
• Assist in preparing internal presentations and status updates.

Collaboration & Engineering Suppor
t

• Participate in code reviews and follow best practices for software quality.
• Work with multidisciplinary engineering teams on workflow integration.
• Support troubleshooting in data pipelines and model execution issues.

Required Qualifications

• Master’s degree completed in the United States (Computer Science, Data Science, ML/AI, Engineering, or related fields).
• Proficiency in Python and core ML libraries (NumPy, Pandas, Scikit-learn).
• Academic or internship experience with model training and evaluation.
• Understanding of ML concepts: bias/variance, evaluation metrics, validation techniques.
• Familiarity with deep learning frameworks (PyTorch or TensorFlow).
• Ability to analyze datasets and communicate insights clearly.
• Strong problem-solving and ability to break down technical tasks.

Preferred Skills

• Experience with LLM APIs or NLP techniques.
• Exposure to cloud ML tools (AWS Sagemaker, GCP Vertex, or Azure ML).
• Understanding of Git-based workflows.
• Experience with SQL or NoSQL databases.
• Exposure to MLOps concepts: Docker, pipelines, model monitoring.

Eligibility

• Must have completed a Master’s degree in the U.S.
• Must be legally authorized to work in the United States.