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- Tasks: Develop and optimise machine learning models while collaborating with a dynamic team.
- Company: Join Google, a leader in tech innovation impacting billions worldwide.
- Benefits: Enjoy flexible work options, competitive pay, and a vibrant company culture.
- Why this job: Be part of cutting-edge projects that shape the future of technology and AI.
- Qualifications: Bachelor's degree with 5 years of relevant experience; advanced degrees preferred.
- Other info: Diversity and inclusion are core values at Google, fostering a welcoming environment.
The predicted salary is between 28800 - 48000 £ per year.
Minimum Qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience with data structures or algorithms and software development in one or more programming languages.
- 3 years of experience testing, maintaining, or launching software products.
- 1 year of experience with software design and architecture.
- Experience with machine learning model pretraining, fine-tuning, evaluation, and optimization methodologies.
- Experience in using common machine learning frameworks such as Tensorflow, PyTorch or Jax.
Preferred Qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- Experience publishing in high-quality machine learning journals.
- Experience in Python and C++.
Responsibilities:
- Write and test product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Design and implement solutions in one or more specialized machine learning areas, leverage or build machine learning infrastructure, and manage machine learning project life-cycle.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
Research Engineer, Fitbit, AI/ML employer: Google
Contact Detail:
Google Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer, Fitbit, AI/ML
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning. Being well-versed in current trends and technologies will not only boost your confidence but also help you engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of AI/ML, especially those who work at Google or similar companies. Attend industry conferences, webinars, or local meetups to make connections that could lead to referrals or insider information about the role.
✨Tip Number 3
Brush up on your coding skills, particularly in Python and C++. Practising coding challenges on platforms like LeetCode or HackerRank can help you prepare for technical interviews where you'll need to demonstrate your problem-solving abilities.
✨Tip Number 4
Prepare to discuss your past projects in detail, especially those involving machine learning. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your experience and problem-solving skills.
We think you need these skills to ace Research Engineer, Fitbit, AI/ML
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data structures, algorithms, and software development. Emphasise your proficiency in programming languages relevant to the role, such as Python and C++, and include any machine learning frameworks you've worked with.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and how your background aligns with Google's mission. Mention specific projects or experiences that demonstrate your skills in machine learning model pretraining, fine-tuning, and evaluation.
Showcase Relevant Projects: Include a section in your application that details any relevant projects you've worked on, especially those involving machine learning. Highlight your contributions, the technologies used, and the outcomes of these projects.
Prepare for Technical Questions: Anticipate technical questions related to software design, architecture, and machine learning methodologies. Be ready to discuss your problem-solving approach and provide examples from your past experiences.
How to prepare for a job interview at Google
✨Showcase Your Technical Skills
Be prepared to discuss your experience with data structures, algorithms, and software development. Highlight specific projects where you used programming languages like Python or C++, and be ready to explain your approach to testing and maintaining software products.
✨Demonstrate Machine Learning Expertise
Since the role focuses on AI/ML, make sure to talk about your experience with machine learning frameworks such as TensorFlow, PyTorch, or Jax. Discuss any projects involving model pretraining, fine-tuning, and evaluation methodologies to show your depth of knowledge.
✨Prepare for Problem-Solving Questions
Expect to face technical questions that assess your problem-solving abilities. Practice coding challenges and algorithm questions that are relevant to the job. This will help you demonstrate your analytical skills and ability to think critically under pressure.
✨Emphasise Collaboration and Communication
Google values teamwork, so be ready to share examples of how you've collaborated with peers and stakeholders in past projects. Discuss your experience with design and code reviews, and how you ensure best practices in your work.
