Principal AI Engineer

India·BangaloreFull-timelead

Machine Learning EngineerData

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Overview

This role is for one of Weekday’s clientsSalary range: Rs 6000000 - Rs 8000000 (ie INR 60 - 80 LPA) Min Experience: 6+ yearsLocation: Bengaluru, KA,

Technical Tools

Machine Learning EngineerData

~1 min read

6–12 years of relevant experience in machine learning, data science, AI engineering, or applied research.
A PhD in a relevant technical discipline is required.
Demonstrated experience delivering innovative ML solutions in research or production environments.

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Design, develop, and deploy advanced machine learning models for complex real-world problems.
Apply expertise in supervised and unsupervised learning, deep learning, statistical modeling, and optimization techniques.
Develop robust model training, validation, testing, and evaluation frameworks.
Analyze large and complex datasets to identify patterns, generate insights, and improve model performance.
Optimize models for accuracy, scalability, computational efficiency, and production readiness.

Lead data science initiatives involving statistical analysis, predictive modeling, experimentation, and feature engineering.
Investigate emerging research papers, algorithms, and AI methodologies to identify opportunities for innovation.
Design and conduct experiments to validate hypotheses and evaluate alternative modeling approaches.
Translate research findings into practical solutions that deliver measurable business value.
Establish reproducible experimentation practices and document technical findings.

Design scalable architectures for machine learning pipelines, model-serving infrastructure, and data processing systems.
Collaborate with software and platform engineering teams to integrate ML models into production applications.
Establish standards for model versioning, monitoring, testing, deployment, and performance optimization.
Address challenges related to data quality, model drift, reliability, latency, and scalability.
Promote responsible AI practices, including model interpretability, fairness, privacy, and security.

Provide technical direction and mentorship to machine learning engineers, data scientists, and researchers.
Collaborate with product managers and business stakeholders to define AI opportunities and technical requirements.
Evaluate new tools, frameworks, and research developments to guide technology decisions.
Communicate complex technical concepts and research outcomes clearly to technical and non-technical audiences.

Strong expertise in machine learning, statistical modeling, and data science.
PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a closely related quantitative field.
Strong programming skills in Python and experience with relevant ML libraries such as PyTorch, TensorFlow, or scikit-learn.
Deep understanding of model evaluation, optimization, experimentation, and algorithm development.
Ability to solve complex technical problems and translate research into deployable solutions.

Experience in AI architecture, distributed ML systems, and production-scale AI deployment.
Research publications, patents, or contributions to open-source AI projects.
Familiarity with generative AI, large language models, and advanced deep learning techniques.
Experience with cloud platforms, MLOps, and model monitoring frameworks.