Software Development Manager - Machine Learning

**Key Responsibilities**

People management - Lead a team of software engineers, DS, DE, MLE, in the design, development, and delivery of software solutions.

Program management - Strong program leader that has run program management functions to efficiently deliver ML projects to production and manage its operations.

• Work with Business stakeholders & customers in the Retail Business domain to execute the product vision using the power of AI/ML.
• Scope out the business requirements by performing necessary data-driven statistical analysis.
• Set goals and, objectives using proper business metrics and constraints.
• Conduct exploratory analysis on large volumes of data, understand the statistical shape, and use the right visuals to drive & present the analysis.
• Analyse and extract relevant information from large amounts of data and derive useful insights on a big-data scale.
• Create labelling manuals and work with labellers to manage ground truth data and perform feature engineering as needed.
• Work with software engineering teams, data engineers and ML operations team (Data Labellers, Auditors) to deliver production systems with your deep learning models.
• Select the right model, train, validate, test, optimise neural net models and keep improving our image and text processing models.
• Architecturally optimize the deep learning models for efficient inference, reduce latency, improve throughput, reduce memory footprint without sacrificing model accuracy.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
• Create and enhance model monitoring system that could measure data distribution shifts, alert when model performance degrades in production.
• Streamline ML operations by envisioning human in the loop kind of workflows, collect necessary labels/audit information from these workflows/processes, that can feed into improved training and algorithm development process.
• Maintain multiple versions of the model and ensure the controlled release of models.
• Manage and mentor junior data scientists, providing guidance on best practices in data science methodologies and project execution.
• Lead cross-functional teams in the delivery of data-driven projects, ensuring alignment with business goals and timelines.
• Collaborate with stakeholders to define project objectives, deliverables, and timelines.

**Skills required: **

• MS/PhD from reputed institution with a delivery focus.
• 5+ years of experience in data science, with a proven track record of delivering impactful data-driven solutions.
• Delivered AI/ML products/features to production.
• Seen the complete cycle from Scoping & analysis, Data Ops, Modelling, MLOps, Post deployment analysis.
• Experts in Supervised and Semi-Supervised learning techniques. Hands-on in ML Frameworks - Pytorch or TensorFlow.
• Hands-on in Deep learning models. Developed and fine-tuned Transformer based models. (Input output metric, Sampling technique)
• Deep understanding of Transformers, GNN models and its related math & internals.
• Exhibit high coding standards and create production quality code with maximum efficiency.
• Hands-on in Data analysis & Data engineering skills involving Sqls, PySpark etc.
• Exposure to ML & Data services on the cloud AWS, Azure, GCP Understanding internals of compute hardware - CPU, GPU, TPU is a plus.
• Can leverage the power of hardware accel to optimize the model execution —PyTorch Glow, cuDNN, is a plus.