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Machine Learning Lead

Country:United States of AmericaLocation:CANHQ: CCS HQ - Syracuse, NY 6304 Carrier Parkway , East Syracuse, NY, 13057 USACarrier is the leading global provider of healthy, safe and sustainable building and cold chain solutions with a world-class, diverse workforce with business segments covering HVAC, refrigeration, and fire and security. We make modern life possible by delivering safer, smarter and more sustainable services that make a difference to people and our planet while revolutionizing industry trends. This is why we come to work every day. Join us and we can make a difference together.About This Role:Carrier is seeking a technical lead for the development and deployment of Machine Learning (ML), Artificial Intelligence and Data Analytics technologies and toolsets across Carrier.Key Responsibilities:• Perform hands-on development.• Lead the development and deployment of diagnostics, machine learning, artificial intelligence and model-based data analytics technology, methods, and toolset.• Develop and execute the overall model-based data analytics strategy & roadmap.• Provide support and guidance to various technical teams, and create common work practices.You Must Have:• Master’s degree or Ph.D. in Computer Science or Computer Engineering or Electrical Engineering or Mechanical Engineering or Chemical Engineering.• 3+ years of experience in leading data analytics projects.• 5+ years of experience in Artificial Intelligence or Machine Learning techniques in the development/deployment of end-to-end analytic solutions.• 5+ years of experience in data processing, simulation based on physics or data driven models and development of reduced order models.We Value:• Proficiency in programming languages such as Python. Hands-on experience with machine learning frameworks/tools/libraries (including scikit-learn, TensorFlow, Keras, PyTorch, Hugging Face Transformers, Langchain, LlamaIndex).• Extensive experience in statistical analysis (including uncertainty analysis), signals processing, machine learning algorithms (classification, regression forecasting, clustering) and AI techniques (probabilistic reasoning, natural language processing, image processing).• Hands-on experience with cloud platforms (AWS, Azure) and related services (EC2, S3, Sagemaker, AWS bedrock, Azure OpenAI).• Experience in Agile methodology for software development and modeling.• Application experience in HVAC and Refrigerating products preferred.Additional Information:• Location: Kennesaw, GA or Syracuse, NY• Travel: Travel up to 10% nationally or internationally may be required.#LI-On-siteRSRCARPay Range:$90,263 - $157,959 AnnuallyCarrier is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.Job Applicant's Privacy Notice:Click on this link to read the Job Applicant's Privacy Notice

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What You Should Know About Machine Learning Lead, Carrier

Carrier is on the hunt for a passionate Machine Learning Lead to join our innovative team in East Syracuse, NY. With our commitment to delivering healthier, safer, and more sustainable solutions, you'll play a crucial role in shaping the future of our technology through the development and deployment of Machine Learning, Artificial Intelligence, and Data Analytics tools. In this position, you'll be hands-on, leading projects that enhance diagnostics and analytics capabilities across our organization. Imagine creating a roadmap that not only improves our technological infrastructure but also drives impactful change within the HVAC and refrigeration industries! We're looking for someone with a master’s or Ph.D. in a relevant engineering or computer science field and several years of experience in artificial intelligence and data analytics projects. If you thrive in a collaborative setting and have a knack for guiding teams, this job might be just right for you. Join Carrier, where your work will not only advance advanced technologies but also lead to a stronger, more sustainable community. Your ideas can help revolutionize industry standards while ensuring modern life runs smoothly. Ready to make a difference? Let’s connect and create impactful solutions together!

Frequently Asked Questions (FAQs) for Machine Learning Lead Role at Carrier
What are the key responsibilities of the Machine Learning Lead at Carrier?

As a Machine Learning Lead at Carrier, you will be responsible for hands-on development and leadership in deploying ML technologies. This includes creating diagnostics tools, developing the overall data analytics strategy, and guiding various technical teams. Your role will focus on revolutionizing our approach to HVAC and refrigeration systems through advanced analytics.

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What qualifications are required for the Machine Learning Lead position at Carrier?

Carrier requires candidates for the Machine Learning Lead role to hold at least a Master’s degree or Ph.D. in Computer Science, Engineering, or related fields, combined with substantial experience in ML techniques. You should also have over 5 years of experience in deploying analytic solutions and leading data analytics projects.

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What programming skills are essential for the Machine Learning Lead role at Carrier?

Candidates for the Machine Learning Lead position at Carrier should be proficient in programming languages, especially Python. Familiarity with machine learning frameworks and libraries like TensorFlow, Keras, and Scikit-learn is essential for effective project execution and collaboration within the team.

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Is experience with cloud platforms necessary for the Machine Learning Lead at Carrier?

Yes, being knowledgeable and experienced with cloud platforms like AWS and Azure is a key requirement for the Machine Learning Lead role at Carrier. Familiarity with related services such as EC2, S3, and Sagemaker will greatly contribute to success in this position, as many data analytics solutions rely heavily on cloud-based technologies.

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What does the travel expectation look like for the Machine Learning Lead at Carrier?

While most of your work as a Machine Learning Lead at Carrier will be based in East Syracuse, NY, some national or international travel may be required, up to 10%. This travel helps facilitate collaboration and innovation across our various teams and locations.

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Common Interview Questions for Machine Learning Lead
Can you describe a machine learning project you led successfully?

When answering this question, focus on your role, the challenges you faced, and the outcomes of the project. Be specific about the technologies used and how you applied machine learning techniques to solve a real-world problem. Highlight your leadership skills and your collaboration with other teams.

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How do you approach debugging and optimizing machine learning algorithms?

Discuss your systematic approach to debugging, including methods for identifying issues in data preprocessing and model performance. Share specific tools and techniques that help you optimize algorithms and improve accuracy, as well as any relevant experiences you've had with algorithm tuning.

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What machine learning frameworks are you most comfortable with?

List the frameworks you have experience with, such as TensorFlow and PyTorch, and discuss what projects you've used them for. Provide examples of how you utilized these tools to capitalize on their strengths in your work.

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How do you ensure the accuracy and reliability of your machine learning models?

Explain the methods you use for validation, such as cross-validation techniques and performance metrics evaluation. Talk about your approach to model testing, understanding potential biases, and how you adjust your models based on empirical feedback.

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What is your experience with cloud computing and its role in machine learning?

Discuss your experience with cloud platforms, particularly focusing on services utilized for machine learning. Emphasize how leveraging cloud technology has enhanced your projects, including aspects like scalability and efficiency in deployment.

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Describe a time when you had to lead a team in a complex project. What challenges did you face?

Provide a specific example that illustrates your leadership qualities. Discuss the team dynamics, the challenges encountered, and how you facilitated communication and collaboration to drive the project to success.

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How do you stay updated on advancements in machine learning and AI?

Share your strategies for staying current in the field, whether through academic journals, attending conferences, participating in online communities, or engaging in continued education. Highlight any specific resources you find particularly valuable.

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What are your thoughts on the ethical considerations surrounding machine learning?

Express your understanding of ethical implications in ML, such as bias, transparency, and privacy. Discuss how you take these factors into account in your work and the importance of developing responsible AI solutions.

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Can you explain how you approach collaboration with cross-functional teams?

Illustrate your collaboration style by discussing communication techniques, interdisciplinary engagement, and tools you use for project management. Share insights on how you build relationships with team members from different backgrounds.

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What role does data preprocessing play in your machine learning workflow?

Explain the significance of data preprocessing in improving model performance. Share specific steps you take, such as handling missing data, normalization, and feature engineering. Provide an example of how diligent preprocessing led to a better outcome in one of your projects.

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The values that we hold high at Carrier underscore how we will serve our customers and shareholders to position the company for future growth. We are committed to always operating with integrity in everything we do. We will continue to be innovato...

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Full-time, on-site
DATE POSTED
December 18, 2024

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