Job Title: Artificial Intelligence/Machine Learning Engineer II
Location: Hybrid - Austin, TX (2 days a week onsite)
Role type: 12 Months contract
Rate: $65-$75/hr
Job Overview
We are seeking a talented and innovative AI / Machine Learning Engineer to join our team. As part of the AI Technical Team, you will design, build, and deploy advanced machine learning models and AI solutions to solve real-world problems. You will work with large datasets, AI/ML frameworks, and cross-functional teams to deliver impactful results that align with our business goals. If you are passionate about machine learning, artificial intelligence, and creating high-performance models, we’d love to hear from you.
Key Responsibilities
- Model Development and Design: Develop, test, and optimize machine learning models for classification, regression, clustering, or recommendation tasks.
- Data Preparation: work alongside the Enterprise Data Management Team to collect, clean, preprocess, and analyze large datasets to create high-quality training datasets.
- Algorithm Implementation: Implement machine learning algorithms and neural networks using frameworks like TensorFlow, PyTorch, and scikit-learn.
- Deployment and Integration: Deploy trained models into production environments using APIs, containers (e.g., Docker), or cloud services (AWS, GCP, or Azure).
- Performance Monitoring: Monitor model performance, detect drift, and implement improvements or retraining strategies to ensure models remain accurate over time.
- Collaboration: Work closely with our data management team, applications team, enterprise architects, and product managers to align solutions with business needs.
- Documentation: Create thorough documentation for models, processes, and experiments to ensure reproducibility and scalability.
- MLOps Practices: Develop automated pipelines for continuous integration, delivery, and model retraining (CI/CD).
- Ethics and Compliance: Ensure AI models comply with industry regulations, address biases, and adhere to ethical standards.
Required Skills & Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.
- Programming Skills: Proficiency in Python, R, or similar programming languages.
- Machine Learning Frameworks: Experience with TensorFlow, PyTorch, Keras, or scikit-learn.
- Data Handling: Strong understanding of SQL, NoSQL, and big data tools (e.g., Spark, Hadoop).
- Cloud Platforms: Familiarity with AWS, Google Cloud, or Microsoft Azure for deploying ML models.
- Model Evaluation: Expertise in using metrics like accuracy, precision, recall, RMSE, or AUC-ROC for performance evaluation.
- Version Control: Experience with GitHub, GitLab, or other version control tools.
- Problem Solving: Strong analytical and problem-solving skills.
- Communication: Ability to explain complex AI/ML concepts to non-technical stakeholders.
