Asks for

The ad says“8–10 years of experience in AI/ML development, advanced analytics, or data‑driven software engineering.”
The ad says“8–10 years of experience in AI/ML development, advanced analytics, or data‑driven software engineering.”
The ad says“Strong understanding of distributed computing, microservices, APIs, and data engineering concepts.”
The ad says“Experience with cloud-based AI/ML platforms such as AWS SageMaker, Azure ML, or Google Vertex AI.”
The ad says“Experience with cloud-based AI/ML platforms such as AWS SageMaker, Azure ML, or Google Vertex AI.”
The ad says“Familiarity with MLOps tools and practices including CI/CD, model registries, feature stores, and monitoring frameworks.”
The ad says“Excellent communication and storytelling skills for conveying complex AI concepts to technical and non‑technical audiences.”
The ad says“Deep expertise in machine learning algorithms, statistical modeling, neural networks, NLP, or computer vision.”
The ad says“Strong understanding of distributed computing, microservices, APIs, and data engineering concepts.”
The ad says“8–10 years of experience in AI/ML development, advanced analytics, or data‑driven software engineering.”
The ad says“Strong understanding of distributed computing, microservices, APIs, and data engineering concepts.”
The ad says“Strong understanding of GenAI techniques, including LLMs, embeddings, vector databases, and prompt‑engineering concepts.”
The ad says“Strong understanding of GenAI techniques, including LLMs, embeddings, vector databases, and prompt‑engineering concepts.”
The ad says“Experience with cloud-based AI/ML platforms such as AWS SageMaker, Azure ML, or Google Vertex AI.”
The ad says“Knowledge of ML security, governance, and responsible AI guidelines is a plus.”
The ad says“Strong proficiency in Python and experience with AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Keras etc.”
The ad says“Strong understanding of GenAI techniques, including LLMs, embeddings, vector databases, and prompt‑engineering concepts.”
The ad says“Deep expertise in machine learning algorithms, statistical modeling, neural networks, NLP, or computer vision.”
The ad says“Demonstrated ability in mentoring and guiding the technical teams.”
The ad says“Strong understanding of distributed computing, microservices, APIs, and data engineering concepts.”
The ad says“Knowledge of ML security, governance, and responsible AI guidelines is a plus.”
The ad says“Familiarity with MLOps tools and practices including CI/CD, model registries, feature stores, and monitoring frameworks.”
The ad says“Deep expertise in machine learning algorithms, statistical modeling, neural networks, NLP, or computer vision.”
The ad says“Deep expertise in machine learning algorithms, statistical modeling, neural networks, NLP, or computer vision.”
The ad says“Strong proficiency in Python and experience with AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Keras etc.”
The ad says“Strong proficiency in Python and experience with AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Keras etc.”
The ad says“Strong problem‑solving and decision‑making capabilities, especially in ambiguous or fast‑changing environments.”
The ad says“Strong understanding of GenAI techniques, including LLMs, embeddings, vector databases, and prompt‑engineering concepts.”
The ad says“Strong proficiency in Python and experience with AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Keras etc.”
The ad says“Strong proficiency in Python and experience with AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Keras etc.”
The ad says“Knowledge of ML security, governance, and responsible AI guidelines is a plus.”
The ad says“Strong proficiency in Python and experience with AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Keras etc.”
The ad says“Proficiency with SQL and experience working with large, complex datasets.”
The ad says“Strong stakeholder management and the ability to collaborate effectively across functions.”
The ad says“Deep expertise in machine learning algorithms, statistical modeling, neural networks, NLP, or computer vision.”
The ad says“Excellent communication and storytelling skills for conveying complex AI concepts to technical and non‑technical audiences.”
The ad says“Strong proficiency in Python and experience with AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Keras etc.”
The ad says“Strong understanding of GenAI techniques, including LLMs, embeddings, vector databases, and prompt‑engineering concepts.”

Be a part of our mission! As a world leader in creating comfortable, sustainable, and efficient climate solutions for buildings, homes and transportation, it's our responsibility to put the planet first. For us at Trane Technologies, and through our businesses including Trane® and Thermo King, sustainability is not just how we do business—it is our business. Do you dare to look at the world's challenges and see impactful possibilities? Do you want to contribute to making a better future? If the answer is yes, we invite you to consider joining us in boldly challenging what's possible for a sustainable world.

Learn about our benefits designed for you to Thrive at work and at home.

We boldly go.

Where is the work:

Monday to Thursday, work onsite with your colleagues. Fridays, choose your work location, balancing what your work requires.

Job Title: Associate Tech Lead – Data Science

Job Summary:
We are seeking a highly skilled Associate Tech Lead specialized in AI/ML to guide the design, development, and deployment of advanced analytical and machine learning solutions. The ideal candidate brings 8–10 years of experience, deep technical expertise across AI/ML systems, and a demonstrated ability to execute high‑impact initiatives from concept to production. This role requires a combination of strong hands‑on technical expertise, and the ability to collaborate across engineering, product, data, and business teams to deliver scalable, innovative AI solutions that drive measurable business value.

Responsibilities:

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

Technical Skills:

Bachelor’s or master’s degree in computer science, Data Science, Engineering, or a related technical field; master’s degree in data science is preferable
8–10 years of experience in AI/ML development, advanced analytics, or data‑driven software engineering.
Deep expertise in machine learning algorithms, statistical modeling, neural networks, NLP, or computer vision.
Strong proficiency in Python and experience with AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Keras etc.
Hands‑on experience designing and deploying ML models into production environments at scale.
Strong understanding of GenAI techniques, including LLMs, 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.
Knowledge of ML security, governance, and responsible AI guidelines is a plus.

Soft Skills:

Demonstrated ability in mentoring and guiding the technical teams.
Excellent communication and storytelling skills for conveying complex AI concepts to technical and non‑technical audiences.
Strong stakeholder management and the ability to collaborate effectively across functions.
Strategic thinker with the ability to define long‑term AI roadmaps while driving short‑term execution.
Strong problem‑solving and decision‑making capabilities, especially in ambiguous or fast‑changing environments.
Highly organized with the ability to manage multiple projects and deliverables simultaneously.
Proactive, innovative mindset with a strong focus on quality, reliability, ethics, and continuous improvement.

We offer competitive compensation and comprehensive benefits and programs. We are an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, age, marital status, disability, status as a protected veteran, or any legally protected status.