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Trane Technologies

Global HVAC and refrigeration efficiency solutions

Tech Lead – Data Science

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

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is required; a Master's degree in Data Science is preferred.
  • 9–12 years of experience in AI/ML development, advanced analytics, or data-driven software engineering.
  • Deep expertise in machine learning algorithms, statistical modeling, neural networks, natural language processing, or computer vision.
  • Strong proficiency in Python and experience with AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, and Keras.
  • Hands-on experience designing and deploying machine learning models into production environments at scale.
  • Strong understanding of generative AI techniques, including large language models, embeddings, vector databases, and prompt-engineering concepts.
  • Proficiency with SQL and experience working with large, complex datasets.
  • Experience with cloud-based AI/ML platforms such as AWS SageMaker, Azure ML, or Google Vertex AI.
  • Familiarity with MLOps tools and practices, including CI/CD, model registries, feature stores, and monitoring frameworks.
  • Strong understanding of distributed computing, microservices, APIs, and data engineering concepts.
  • Proven leadership abilities with experience mentoring and guiding technical teams.
  • Communication and storytelling skills to convey complex AI concepts to technical and non-technical audiences.
  • Stakeholder management and ability to collaborate across functions.
  • Ability to define long-term AI roadmaps while driving short-term execution.
  • Problem-solving and decision-making capabilities, particularly in ambiguous or fast-changing environments.
  • Ability to manage multiple projects and deliverables simultaneously.

Responsibilities

  • Provide technical leadership for end-to-end development of AI/ML systems, from data ingestion and feature engineering through model deployment and monitoring.
  • Define the architectural direction for machine learning platforms, ensuring scalability, security, performance, and alignment with organizational standards.
  • Lead evaluation, selection, and integration of AI technologies, frameworks, and tools, including generative AI solutions.
  • Collaborate with product and domain teams to translate business requirements into machine learning architectures and solution roadmaps.
  • Oversee machine learning model lifecycle management, including experimentation, versioning, CI/CD integration, and continuous improvement.
  • Mentor and guide data scientists, machine learning engineers, and analysts, fostering technical excellence and knowledge sharing.
  • Review machine learning pipelines, code, and solution designs for quality, maintainability, and adherence to best practices.
  • Drive MLOps practices such as automated model training, deployment, monitoring, and retraining workflows.
  • Partner with cross-functional teams to troubleshoot complex machine learning and data pipeline issues and develop long-term solutions.
  • Advise on opportunities to adopt emerging AI/ML and generative AI techniques to accelerate innovation.
  • Integrate data quality, governance, compliance, and responsible AI principles into AI/ML initiatives.
  • Promote continuous improvement and establish best practices in AI architecture, experimentation, model evaluation, and documentation.

Desired Qualifications

  • Knowledge of machine learning security, governance, and responsible AI guidelines.

About the Company

Trane Technologies

Global HVAC and refrigeration efficiency solutions

Trane Technologies focuses on climate innovation by delivering sustainable HVAC and refrigeration solutions through its Trane and Thermo King brands. It helps buildings, homes, and transportation achieve higher energy efficiency with high-performance climate control equipment and ongoing maintenance services. The company differentiates itself by offering an integrated portfolio of energy-efficient products and service contracts across both HVAC and refrigeration, backed by a commitment to sustainability. Its goal is to lower energy use and carbon emissions for customers while supporting a healthier planet.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1871

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