Overview

TalentReach is hiring on behalf of a rapidly growing technology company seeking an experienced Senior Machine Learning Engineer to develop and deploy production-scale machine learning solutions that power intelligent decision-making across a high-volume global platform.

Location

Austin, TX (Hybrid - 4 Days Onsite)

What You'll Do

• •Design, develop, and deploy production machine learning models that solve recommendation, prediction, ranking, and forecasting problems
• •Partner with Product Managers and Engineering teams to translate business challenges into scalable machine learning solutions
• •Build and maintain data pipelines, feature engineering workflows, and model training infrastructure
• •Deploy, monitor, and continuously improve machine learning models in production environments
• •Evaluate model performance using offline experimentation and production metrics while monitoring for model drift
• •Develop scalable infrastructure supporting model serving, orchestration, and continuous deployment
• •Research emerging machine learning techniques and prototype new modeling approaches
• •Conduct experiments to validate model improvements and measure business impact
• •Write high-quality, maintainable, and well-tested production code
• •Collaborate with cross-functional engineering teams to improve machine learning infrastructure and development practices

Required Qualifications

• •Master's or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Artificial Intelligence, or a related quantitative discipline, or equivalent professional experience
• •3+ years of experience building, deploying, and supporting production-grade machine learning systems
• •Strong software engineering skills with experience developing production applications
• •Experience training, tuning, deploying, monitoring, and maintaining machine learning models at scale
• •Strong understanding of modern machine learning techniques, experimentation, and model evaluation
• •Experience building feature engineering pipelines and scalable ML workflows
• •Experience with TensorFlow, PyTorch, or similar machine learning frameworks
• •Strong analytical, problem-solving, and communication skills
• •Ability to work in a hybrid environment with four days per week onsite

Preferred Qualifications

• •Experience with recommendation systems, ranking algorithms, click-through rate prediction, forecasting, or conversion modeling
• •Knowledge of Bayesian methods, multi-task learning, meta-learning, or related machine learning approaches
• •Experience with Kubeflow, feature stores, MLOps platforms, or machine learning orchestration frameworks
• •Familiarity with production model serving and monitoring infrastructure
• •Experience with modern recommendation model architectures or deep learning frameworks
• •Experience designing and evaluating large-scale online and offline machine learning experiments

Compensation and Benefits

• •Target Total Compensation: $335,000 - $400,000
• •Base Salary: $210,000 - $260,000
• •Equity opportunity
• •401(k) with company matching
• •Comprehensive medical, dental, and vision coverage
• •Wellness, technology, mobile, and commuter benefits
• •Catered meals and stocked office
• •Generous paid time off and additional leave programs