Distinguished Engineer - AI/ML Engineering

What youll be doing...

We are seeking an experienced and highly motivated Distinguished Engineer to lead the architecture and design of our Generative AI practice. In this role, you will spearhead the development and implementation of cutting-edge AI/ML solutions, leveraging your deep expertise to drive innovation and establish industry best practices.

• Leading the architectural design and implementation of a robust and scalable Generative AI platform, defining the technology roadmap and strategy.
• Having experience in technical leadership and mentorship to a team of AI/ML engineers, fostering a culture of collaboration and innovation.
• Designing, developing, and deploying end-to-end AI/ML solutions, including data pipelines, model training, deployment, monitoring, and optimization.
• Staying abreast of the latest advancements and trends in Generative AI, continuously evaluating and integrating emerging technologies.
• Collaborating closely with cross-functional teams, including product, engineering, and business stakeholders, to translate business requirements into innovative AI/ML solutions.
• Championing the adoption of AI/ML best practices, ensuring the development and deployment of secure, reliable, and ethical AI systems.
• Having experience on Model-serving runtimes Like BentoML or TensorFlow Serving (TFX) or Triton Inference Server
• Having experience on Model-serving platforms like Cloud-provider platforms (Amazon SageMaker, Vertex AI, Azure Machine Learning) KServe , Ray .

What were looking for:

Youll need to have:

• Bachelors degree or four or more years of work experience.
• Six or more years of relevant work experience.
• Experience in AI/ML engineering, with a strong focus on Generative AI models and techniques (e.g., GANs, VAEs, Diffusion Models).

Even better if you have one or more of the following:

• Masters or Ph.D. degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Proven track record of architecting, designing, and implementing large-scale AI/ML systems in a production environment.
• Deep understanding of cloud computing platforms (e.g., AWS, Azure, GCP) and their AI/ML services.
• Excellent communication, interpersonal, and presentation skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical audiences.
• Experience with MLOps tools and best practices.
• Contributions to open-source AI/ML projects.
• Familiarity with telecommunications industry data and use cases.