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.

As a Senior Machine Learning Engineer, you will own the full machine learning lifecycle, from problem definition and feature engineering through model training, deployment, monitoring, and continuous optimization. You will develop scalable ML systems, evaluate emerging technologies, and help shape the future of intelligent products operating at massive scale.

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