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- Tasks: Design and implement machine learning solutions for diverse customer use cases.
- Company: Join Google Cloud, a leader in digital transformation and innovative technology.
- Benefits: Enjoy flexible work options, travel opportunities, and access to cutting-edge tools.
- Why this job: Shape the future of businesses while working with top-tier clients and advanced technologies.
- Qualifications: Bachelor's degree in Computer Science and 6 years of relevant experience required.
- Other info: Travel up to 30% for on-site customer engagements and workshops.
The predicted salary is between 43200 - 72000 £ per year.
Minimum qualifications:
- Bachelor\’s degree in Computer Science or equivalent practical experience.
- 6 years of experience building machine learning solutions and working with technical customers.
- Experience designing cloud enterprise solutions and supporting customer projects to completion.
- Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C ) including data structures, algorithms, and software design.
Preferred qualifications:
- Experience designing applications powered by Large Language Models and leading their implementation.
- Experience working with recommendation engines, data pipelines, or distributed machine learning.
- Experience with deep learning frameworks (e.g., Tensorflow, pyTorch, XGBoost).
- Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).
- Understanding of contact center technologies and platforms (e.g., Avaya, Genesys, Cisco, Mitel, Twilio, etc.).
- Understanding of the auxiliary practical concerns in production machine learning systems.
About the job
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google\’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.
In this role, you are the Google Engineer working with Google\’s largest and most ambitious Cloud customers. Together with the team you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
Google Cloud accelerates every organization\’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google\’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
- Be a trusted technical advisor to customers and solve machine learning challenges.
- Coach customers on the practical challenges in machine learning systems: feature extraction and feature definition, data validation, monitoring, and management of features and models.
- Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
- Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
- Travel up to 30% for in-region for meetings, technical reviews, and onsite delivery activities as needed.
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Conversational AI Consultant, Google Cloud employer: Google
Contact Detail:
Google Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Conversational AI Consultant, Google Cloud
✨Tip Number 1
Familiarise yourself with Google Cloud's suite of products, especially TensorFlow and Vertex AI. Understanding how these tools work will not only help you in interviews but also demonstrate your commitment to leveraging Google's technology for machine learning solutions.
✨Tip Number 2
Network with professionals in the field of conversational AI and cloud computing. Attend relevant meetups or webinars where you can connect with current Google employees or industry experts. This could provide you with insider knowledge and potentially a referral.
✨Tip Number 3
Showcase your experience with machine learning projects, particularly those involving large language models or recommendation engines. Be prepared to discuss specific challenges you faced and how you overcame them, as this will highlight your problem-solving skills.
✨Tip Number 4
Stay updated on the latest trends and advancements in machine learning and cloud technologies. Being knowledgeable about recent developments will allow you to engage in meaningful conversations during interviews and demonstrate your passion for the field.
We think you need these skills to ace Conversational AI Consultant, Google Cloud
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning solutions, cloud enterprise design, and coding in languages like Python or Java. Emphasise any relevant projects that showcase your skills in these areas.
Craft a Strong Cover Letter: In your cover letter, explain why you're passionate about the role of Conversational AI Consultant at Google Cloud. Mention specific experiences that align with the job description, such as your work with large language models or deep learning frameworks.
Showcase Relevant Projects: Include examples of past projects where you designed and implemented machine learning solutions. Detail your role, the technologies used, and the impact of these projects on the business or customer outcomes.
Highlight Customer Interaction Experience: Since the role involves working closely with customers, emphasise any experience you have in coaching or advising clients on technical solutions. This could include workshops, presentations, or direct project involvement.
How to prepare for a job interview at Google
✨Showcase Your Technical Expertise
Make sure to highlight your experience with machine learning solutions and cloud enterprise designs. Be prepared to discuss specific projects where you implemented these technologies, especially using tools like TensorFlow or Vertex AI.
✨Demonstrate Problem-Solving Skills
Prepare to share examples of how you've tackled complex machine learning challenges in the past. Discuss your approach to feature extraction, data validation, and model management, as these are key aspects of the role.
✨Understand Customer Needs
Research the company’s customer base and their potential needs regarding AI solutions. Be ready to explain how you would tailor machine learning applications to meet those specific requirements.
✨Communicate Clearly and Effectively
As a consultant, you'll need to convey complex technical concepts to non-technical stakeholders. Practice explaining your past projects in simple terms, focusing on the impact and benefits of your solutions.
