Machine Learning Engineer

Company:  Dice
Location: Dallas
Closing Date: 09/11/2024
Salary: £150 - £200 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Enterprise Engineering, is seeking the following. Apply via Dice today!


Machine Learning Engineer


Location: Dallas, Texas (Hybrid Role)


Type: Consulting


Apply only if you can work on W2 with us or if you have an independent corporation.


Experience: 8+ years


  1. Hands-on with code, but able to mentor junior staff.
  2. Design, implement, and optimize machine learning algorithms and models including:
  • Neural networks (Graph neural network)
  • Deep learning & transformers (Temporal Fusion Transformer)
  • NLP
  • Gradient boosting using open source machine learning frameworks (TensorFlow, PyTorch, XGBoost, LightGBM)
  • Enable functionality to support analysis, model optimization, statistical testing, model versioning, deployment, and monitoring of models and data.
  • Ability to translate functionality into scalable, tested, and configurable platform architecture and software.
  • Establish strong software engineering principles for development in Python on the Azure Kubernetes Platform.
  • Strong ownership of deliverables, with design decisions aligned to scale and industry best practices.
  • Collaborate with cross-functional teams to align ML initiatives with overall business goals.
  • Implement scalable and efficient machine learning systems. Collaborate with software engineers to integrate ML models into production systems.
  • Work closely with data engineers to ensure the availability and quality of data for training and evaluation of machine learning models.
  • Develop strategies for deploying machine learning models at scale. Ensure models are integrated into production systems with high reliability and performance.
  • Design and conduct experiments to evaluate the performance of machine learning models. Iterate on models based on feedback and evolving business requirements.
  • Python and SQL hands-on coding experience.
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