Senior Manager Machine Learning (AI)

TL;DR

Senior Manager Machine Learning (AI/Recommendations): Driving the vision and strategy for Commerce Intelligence, focusing on multi-modal search, recommendation systems, and brand/price affinity modeling. Focus on providing technical leadership for architecture, ML approaches, performance monitoring, and production deployments of large-scale recommendation systems.

Location: Bangalore, India. Flexible work arrangement, with office presence encouraged (pet-friendly office).

Company

hirify.global AI is an AI commerce platform shaping the next wave of e-commerce with inspiration-led shopping, part of the InMobi Group, and funded by Google, Jio Platforms, and Mithril Capital.

What you will do

• Define the overall vision for commerce intelligence, focused on up-leveling internal use of machine learning.
• Provide technical leadership for overall architecture, ML approaches, performance monitoring, and production deployments.
• Manage, develop, coach, and mentor a team of machine learning engineers and big data specialists.
• Partner with business and product teams to help predict system behavior, establish metrics, and improve debugging skills.
• Lead data mining and collection procedures, especially focused on unstructured and siloed data sets.
• Drive the implementation of models into production through various engineering teams.

Requirements

• PhD or Master’s in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, Data Science; or bachelor's with additional experience.
• 10+ years of ML related industry experience working on large-scale recommendation systems or personalization.
• 3+ years in a leadership role.
• Deep expertise in applied algorithms, models, and techniques used to design, scale, and optimize large-scale recommendation systems.
• Comfortable with software programming and statistical platforms such as Tensorflow, PyTorch, scikit-learn.
• Comfortable with using one or more distributed training technologies such as Apache Spark, RAPIDS, dask, along with MLOps stack such as kubeflow, mlflow.
• Excellent technical and business communication skills.

Nice to have

• Experience in e-commerce.

Culture & Benefits

• Opportunities to make an immediate impact on mission-critical projects.
• Be rewarded for autonomy while collaborating.
• Leverage bleeding-edge tech to disrupt consumer experiences.
• Daily meals, gym, trainings, and tech tools.
• Regular unwind sessions and a focus on work-life balance.
• Pet-friendly office environment.