Key Responsibilities:

Strategy &amp; Leadership:

<ul>
<li>Define and own the technical roadmap and architectural vision for the entire MLOps lifecycle, from feature engineering to model serving and monitoring.</li>
</ul>

<ul>
<li>Implement the ML platform strategy, overseeing the architecture of core components like the feature store, model registry, and experiment tracking frameworks.</li>
</ul>

<ul>
<li>Collaborate with Engineering, ML, and Insights teams to foster a data-driven culture across the organization.</li>
</ul>

Cross-Functional Collaboration:

<ul>
<li>Collaborate closely with Data Scientists to understand their modeling needs and translate them into robust platform capabilities.</li>
</ul>

<ul>
<li>Engage with key stakeholders across Product, Marketing, and Operations to drive data governance, quality, and compliance.</li>
</ul>

<ul>
<li>Team Leadership:Build and lead high-performing machine learning engineering teams.</li>
</ul>

<ul>
<li>Mentor and guide senior ML engineers on their most complex technical challenges.</li>
</ul>

<ul>
<li>Set and monitor OKRs &amp; KPIs to deliver high-impact, reliable data and ML solutions.</li>
</ul>

Operational Excellence:

<ul>
<li>Ensure the ML platform's reliability, scalability, and cost-effectiveness.</li>
</ul>

<ul>
<li>Oversee the platform's performance and resource utilization, proactively identifying and resolving bottlenecks.</li>
</ul>

<ul>
<li>Optimize cloud infrastructure (preferably on Azure) for efficiency and performance.</li>
</ul>

Innovation:

<ul>
<li>Stay ahead of industry trends and the latest advancements in AI/ML, such as LLMs, Generative AI, and new MLOps tools.</li>
</ul>

<ul>
<li>Drive research and development efforts and lead Proof of Concepts (POCs) to introduce new technologies that solve Myntra’s unique business problems.</li>
</ul>

Requisites:

<ul>
<li>A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related ML field.</li>
</ul>

<ul>
<li>14+ years of professional experience in software or data engineering, with at least 5+ years in a senior leadership role managing a large team.</li>
</ul>

<ul>
<li>A minimum of 5+ years of specific, hands-on experience as a Machine Learning Engineer is required.</li>
</ul>

<ul>
<li>Proven experience (minimum 3 years) in an architect or lead role focused on building and scaling ML platforms.</li>
</ul>

<ul>
<li>Experience in a high-scale e-commerce or tech-driven company is highly preferred.</li>
</ul>

<ul>
<li>Deep MLOps Expertise: Proven, hands-on experience designing and implementing a complete MLOps stack in a production environment.</li>
</ul>

<ul>
<li>Big Data &amp; Feature Engineering: Expertise with distributed data processing technologies like Apache Spark. Experience designing and building feature stores is required.</li>
</ul>

<ul>
<li>Cloud and Distributed Systems: Strong knowledge of a major cloud platform (preferably Microsoft Azure/GCP) and a deep understanding of distributed systems architecture.</li>
</ul>

<ul>
<li>Orchestration &amp; Deployment: Strong understanding of containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for ML models.</li>
</ul>

<ul>
<li>ML Frameworks: In-depth, hands-on knowledge of popular ML frameworks such as PyTorch, TensorFlow, and scikit-learn.</li>
</ul>

<ul>
<li>Generative AI: Hands-on experience with modern Generative AI technologies, including Large Language Models (LLMs), RAG, and vector databases.</li>
</ul>

<ul>
<li>Technical Leadership: A proven track record of leading engineering teams, defining architectural best practices, and driving impactful technical decisions.</li>
</ul>

Machine Learning Engineering in Bengaluru (UID-12306)

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Job Description for Machine Learning Engineering

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