Azure
6 months ago
**Responsibilities**:
Have technical discussions with the customer with a discovery mindset, understanding their use-case, technical infrastructure, cloud infrastructure, ML tooling and future goals.
Digest the information on a product feature scope and document, share and plan future advisories from here.
Assist on compute on both levels - planning for current optimal usage and future scope, as well as getting those allocated through the available and pre-decided channels.
Advise startups on blockers for scenarios - not restricted to but including cost optimization of ML workloads, optimal use of infrastructure, right way of fine-tuning or inferencing on ML platform.
Advise startups proactively on features and open-source software supported by Azure that the startup can think about for their current infrastructure.
Provide reporting on the above on a weekly basis and ensure project management independently.
Be able to take decisions or escalate matter suitably, as per the needs of the account.
Guide fellow advisors on topics they’d need help with.
**Skills**:
Understanding of, or curiosity to ramp up on, Azure AI infrastructure, platform, and services on L300-400
Experience of having handled ML specific requests and/or solution build for startups
Ability to understand and deep dive on ML pipeline, ML Ops and data ingestion as it refers to Azure ML.
Ability to gear up on applied AI services like Azure OpenAI Service on L400 and consult with startups about fine-tuning, simple prompt engineering etc.
Ability to understand the magnitude of ML pipeline in terms of data set size, intensive training, compute involved etc, to have a planning discussion with the startup.
Ability to carry weekly discussions and report out on highs, lows and blockers.
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