Director of AI Solutions & Engineering
Digital Realty
AirflowAzureCloudDockerJavaScriptKubernetesNext.jsPyTorchReactScikit-LearnTensorflow
Job Level
Senior
Tech Stack
AngularAzureCloudDockerGoGraphQLNumpyPandasPythonPyTorchReactScikit-LearnTensorflow
About the role
- Design, build, and deploy machine learning models and algorithms; optimize models for performance and scalability.
- Work with large data sets to preprocess, clean, and transform data and develop and maintain data pipelines.
- Monitor and evaluate performance of deployed models; make adjustments and improvements to ensure accuracy and reliability.
- Collaborate with data scientists, analysts, and product managers to understand requirements and deliver ML solutions.
- Keep up with latest research and trends in machine learning and AI; explore and implement new techniques to enhance model performance.
- Document model development processes, code, and standard methodologies; provide clear reports on model performance and metrics.
- Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint Retrospective.
Requirements
- Bachelor’s degree in computer science, Data Science, Statistics, or a related field; master's degree or higher preferred.
- More than 5 years of experience in machine learning engineering or a related role.
- Proficiency in programming languages such as Python or R.
- Experience with machine learning frameworks (e.g., Go, TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers, LangChain, or similar).
- Experience designing and optimizing prompts for large language models (LLMs); Multimodal AI.
- Proficiency in React, Angular for building interactive AI-powered UIs.
- Experience integrating ML models into web applications using REST APIs, WebSockets, or GraphQL.
- Ability to fine-tune foundation models on domain-specific data.
- Understanding of ethical AI, bias mitigation, and model interpretability in generative systems.
- Deep understanding of transformer-based models (e.g., GPT, LLaMA, Claude), diffusion models, and GANs.
- Experience with LangChain, Semantic Kernel, AutoGen, or similar frameworks for building AI agents.
- Designing agents that can plan, reason, and interact with APIs, databases, and external tools.
- Experience with data processing tools (e.g., pandas, NumPy).
- Strong analytical and problem-solving skills.
- Experience deploying machine learning models to production, including containerization (e.g., Docker) and cloud platforms; Microsoft Azure preferred.
- Hands-on experience with Azure Machine Learning, Azure OpenAI, Azure Cognitive Services, and Azure Functions.
- Excellent verbal and written communication skills.
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