Senior Machine Learning (AI) Developer, Cyber

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Requirements:

• 5+ years of experience with the following ML model techniques: LLMs, Deep Learning, traditional ML and predictive modeling.
• 5+ years of experience with Python programming.
• 3+ years experience with building, validating, deploying and monitoring production models.
• Strong skills in using generative AI to speed up features delivery.
• Strong understanding of Generative AI techniques and models.
• Experience with ML frameworks such as Tensorflow, PyTorch.
• Experience with infrastructure and tooling for MLOps.
• Excellent communication and collaboration skills.

Responsibilities:

• Package LLM models, incorporating Generative AI, deploy to production environments, and monitor usage and performance.
• Collaborate with engineers and product managers to integrate Generative AI features into existing systems.
• Experiment with different Generative AI techniques and architectures to optimize both delivery and performance.
• Evaluate and validate the effectiveness of Generative AI models using appropriate metrics.
• Manage ML infrastructure in the cloud.
• Test models at scale and ensure CI/CD best practices are followed by the whole team.
• Diagnose and resolve ML workflow and production issues quickly.
• Design, develop, and maintain machine learning algorithms that work on machines with limited resources as well as in cloud environments.
• Create and maintain scalable feature pipelines.
• Integrate the algorithms in the current systems, in collaboration with the engineering teams.
• Write production-level code to convert ML models into working pipelines.
• Correct anomalies and problems as they arise.
• Test the implemented features to make sure all acceptance criteria are met.
• Participate in projects from the initial idea to launch.
• Contribute to the continuous improvement of development activities (agility, automated tests, deployment, etc.).
• Collaborate with the security team to integrate security best practices into software development processes.
• Communicate risks associated with any activity, technology, or processes as you identify them.
• Stay up to date with developments in the machine learning industry.