- Senior Machine Learning Engineers needed for high growth tech company
- Austin, TX - must be willing to work in office 4 days a week
- High competitive salary + equity + strong benefits
Senior Machine Learning EngineerWe're partnering with a fast-growing technology company that's building machine learning systems at significant scale to solve complex real-world challenges. Their platform processes billions of transactions annually and uses advanced AI to power intelligent decision-making for millions of end users.
As a Senior Machine Learning Engineer, you'll work at the intersection of machine learning and software engineering, collaborating closely with product and engineering teams to design, build and deploy production-grade ML models that directly influence business outcomes.
Compensation - Total compensation: $335k-$400k
- Base salary: $210k-$260k
- Equity package included
- Comprehensive benefits
What you'll do - Partner with product managers and engineers to translate business problems into scalable machine learning solutions.
- Design, develop and deploy production-ready machine learning models across areas such as ranking, prediction, optimisation, forecasting and recommendation.
- Build robust data pipelines, engineer high-quality features and integrate models into scalable production infrastructure.
- Monitor model performance, detect drift and continuously improve model accuracy through retraining and experimentation.
- Write clean, well-tested, production-quality code and contribute to engineering best practices across testing, reliability and performance.
- Research emerging machine learning techniques, prototype new approaches and validate ideas through offline and online experimentation.
What we're looking for - PhD or Master's degree in Computer Science, Statistics, Mathematics or a related quantitative discipline (or equivalent industry experience).
- Strong background in machine learning and software engineering with experience delivering production ML systems.
- Expertise in one or more of the following areas:
- Recommender systems
- Bayesian machine learning
- Multi-task learning
- Meta-learning
- Ranking, prediction or optimisation models
- At least 3 years of experience building end-to-end machine learning systems, including training, deployment, serving and monitoring.
- Experience with modern ML infrastructure such as TensorFlow, Kubeflow (or similar) and feature stores is highly desirable.
- Familiarity with large-scale deep learning architectures used for recommendation or ranking systems is a plus.
Working arrangements - Hybrid working model with four days per week in the office and one day working remotely.
This is an opportunity to join a highly technical engineering team where machine learning sits at the core of the product. You'll have the chance to work on challenging problems at scale, collaborate with experienced engineers and researchers, and see your work make a measurable impact.
