Senior Machine Learning Engineering
4 hours ago
The Software Engineering team delivers next-generation application enhancements and new products for a changing world. Working at the cutting edge, we design and develop software for platforms, peripherals, applications and diagnostics — all with the most advanced technologies, tools, software engineering methodologies and the collaboration of internal and external partners.
Join us to do the best work of your career and make a profound social impact as a
Senior Machine Learning Engineer
on our
Software Engineering Team
in our
Client Solutions Group
.
What You'll Achieve:
As a Senior Machine Learning Engineer, you will be responsible for designing, developing, and deploying machine learning models that power intelligent tools and features across our products. This role requires strong technical expertise, a collaborative mindset, and a passion for solving real-world problems using data.
You will:
- Design and implement AI algorithms and models for real-world applications (e.g., NLP, computer vision, recommendation systems).
- Collaborate with cross-functional teams to integrate AI solutions into products and services.
- Optimize and scale machine learning models for performance and efficiency.
- Maintain and improve existing AI systems through continuous learning and feedback loops.
- Conduct research and stay up-to-date with the latest advancements in AI and machine learning.
- Write clean, maintainable, and well-documented code.
- Participate in code reviews, testing, and deployment processes.
Essential Requirements
- 8+ years of combined experience in the architecture, design and development of BIOS Firmware , Artificial Intelligence, Machine Learning, or related field with Bachelor's or Master's degree.
- Strong programming skills in Python (preferred), C++, or Java.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Solid understanding of data structures, algorithms, and software engineering principles.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes).
- Experience and deep learning, reinforcement learning, or generative models.
- Knowledge of MLOps practices and tools.
- Prior experience deploying AI models in production environments preferred.
- Contributions to open-source AI projects or published research preferred.
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