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o9 Solutions

Integrated planning platform for demand forecasting

Senior Software Architect 2

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A Master's or PhD in Computer Science, Applied Mathematics, Statistics, Physics, or a closely related quantitative discipline is required.
  • At least 10 years of overall software engineering experience is required.
  • At least 5 years of hands-on experience in applied mathematics, statistical modeling, and deep learning systems is required.
  • Demonstrated experience architecting and deploying AI solutions in production environments is required.
  • Strong experience designing, training, and deploying deep learning models using modern AI frameworks is required.
  • A solid understanding of the full machine learning lifecycle, including experimentation, deployment, monitoring, and retraining, is required.
  • Experience working with large datasets and distributed or high-performance computing environments is required.
  • Deep expertise in linear algebra, multivariate calculus, probability theory, optimization, statistical modeling, and causal inference is required.
  • The ability to reason formally about model behavior, convergence, and performance trade-offs is required.
  • Expert-level proficiency in Python, including state-of-the-art mathematical, statistical, machine learning, and agentic libraries, is required.
  • Strong software engineering fundamentals in data structures, algorithms, system design, and performance optimization are required.

Responsibilities

  • Own the end-to-end mathematical and statistical architecture of complex AI systems, from data integration and feature engineering to model training, inference, and monitoring.
  • Design scalable, robust, and secure AI models and algorithms capable of handling large-scale, complex enterprise systems, grounded in first-principles mathematical design.
  • Establish architectural standards, design principles, and best practices for AI-centric systems across the organization.
  • Translate business and domain problems into mathematical, statistical, and agentic models.
  • Apply techniques from linear algebra, optimization, numerical methods, statistics, and causal inference to improve model robustness and performance.
  • Guide teams in selecting modeling approaches, loss functions, evaluation metrics, and validation strategies.
  • Design, develop, and deploy advanced deep learning models, including transformers, state-space models, and diffusion models.
  • Oversee the full model lifecycle, including experimentation, training, evaluation, deployment, and continuous improvement.
  • Ensure models are production-ready, explainable where required, and aligned with business objectives.
  • Optimize models and pipelines for speed, scalability, memory and compute efficiency, and accuracy.
  • Apply pruning, quantization, distributed training, and GPU or accelerator optimization techniques.
  • Collaborate with platform and infrastructure teams to maximize system-level performance.
  • Act as a technical mentor and thought leader for AI engineers, AI scientists, and software developers.
  • Review designs, code, and models, providing guidance on architecture, quality, and maintainability.
  • Promote best practices in model design, algorithm development, coding, testing, and documentation to elevate modeling maturity.
  • Evaluate, select, and evolve AI frameworks, libraries, tools, and cloud platforms.
  • Stay current with cutting-edge research, industry trends, and emerging technologies in AI and applied mathematics.
  • Identify opportunities to apply advanced AI techniques to business challenges and drive innovation.

Desired Qualifications

  • Experience with additional programming languages such as Scala, Kotlin, or Rust is highly desirable.

About the Company

o9 Solutions

Integrated planning platform for demand forecasting

o9 Solutions provides an integrated planning platform for enterprise-wide planning across supply chain, retail, finance, and operations. The platform uses AI/ML forecasting, collaborative demand planning, demand sensing, and scenario evaluation, with near real-time production scheduling embedded into workflows. It differentiates itself by offering a single, end-to-end platform that unifies planning and analytics across multiple functions, enabling fast scenario analysis and synchronized execution. The goal is to help businesses quickly respond to market changes, improve planning accuracy, and keep the organization aligned with strategic targets.

Company size
1,001-5,000
Company stage
Growth Equity (Venture Capital)
Total funding
$533M
Headquarters
Farmers Branch, TX
Founded
2009

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