Company Overview
Join a high-impact technology company revolutionizing real-time prediction and data-driven systems. Though leaders in detecting complex patterns in decentralized data, our core innovations remain undiscovered by much of the ecosystem your work will help change that.
Role Overview
Youll design, build, deploy, and maintain scalable ML systems that power critical insights and automation. Working cross-functionally, you'll translate complex models into production-ready solutions that deliver real-world impact.
Key Responsibilities
- Design and implement ML and deep learning models for real-time prediction systems
- Prepare and preprocess large, complex data sets apply feature engineering and data transformations
- Collaborate with data scientists and engineers to convert prototypes into robust, production-grade pipelines
- Deploy, monitor, and maintain model strack performance and retrain as needed to ensure reliability
- Conduct experiments, hyper parameter tuning, and performance evaluations
Design scalable infrastructure to support ML workflows (e.g., pipeline orchestration, model serving
- Communicate findings, limitations, and data-driven insights clearly to non-technical stakeholders Stay current with developments in frameworks and methodologies (TensorFlow, PyTorch, scikit-learn, etc.)
Required Qualifications
- Proven experience as an ML Engineer or similar (2+ years preferred)
- Strong programming skills in Python (and optionally Java, R)
- Deep understanding of statistics, linear algebra, probability, and ML algorithms Proficiency with ML libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, Keras
- Experience building ML pipelines and deploying models in production
- Strong communication skills, with proven ability to explain technical concepts to diverse audiences
- Bachelors degree in Computer Science, Statistics, Mathematics, or related field (Masters a plus)
