Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead machine learning projects to enhance Unity's ad optimization and strategy.
- Company: Unity is a fast-growing company focused on empathy, respect, and opportunity in tech.
- Benefits: Enjoy a collaborative environment with opportunities for innovation and impact.
- Why this job: Join a team at the forefront of machine learning, making a real difference in the industry.
- Qualifications: PhD or equivalent experience in a technical field; expertise in ML frameworks required.
- Other info: Be part of a mission-driven team that values creativity and research.
The predicted salary is between 54000 - 84000 £ per year.
Principal Applied Research Machine Learning Engineer
At Unity, our Inclusion is driven by one overarching framework: Empathy, Respect, and Opportunity. In a collaborative, fast-growing environment, we are solving hard problems and enabling the success of our community. At Unity, you will make a difference. In the Unity Ads Applied Research team, we envision and build systems that help creators capture the value they build!
Come join Unity’s Ads Applied Research team to help drive the overall Ads strategy for Unity’s products and services. In this position, you’ll be driving our applied research and analysis on how to improve the optimization and machine learning powering our ad networks, marketplace, and audience tools.
RESPONSIBILITIES
- As a machine learning and data science expert, you will guide and drive the application of machine learning solutions across the whole organization. Your role will be to:
- Define and execute advanced machine learning models and algorithms to help translate complex business problems.
- Be at the forefront of the latest machine learning research to improve Unity’s Ad platform Machine Learning capabilities.
- Optimize, improve, and innovate ML practices to establish Unity as an industry leader.
- Form and validate hypotheses on new aspects of modeling and the potency of new datasets for ML.
- Drive optimization hypotheses by analyzing the drivers for impactful machine learning and arguing the hypotheses and success for the next steps of development.
- Communicate data and machine learning capability needs to the product and engineering teams as the authority in Data for ML.
- Drive the overall direction of the machine learning future for Ads to support strategic goals and vision.
REQUIREMENTS
- We are looking for a candidate with experience in guiding machine learning development via revolutionary steps to keep Unity Ads at the forefront of ML performance.
- PhD in Computer Science, Mathematics, Statistics, or a related technical field, or equivalent experience in interpreting and translating research to applications.
- Experience successfully taking research and turning it into concrete product innovations with impact.
- Expertise with modeling frameworks (e.g., TensorFlow, PyTorch) and understanding of model architectures and mechanisms.
- Ability to explain machine learning and interpret the modeling efficacy for further improvements.
- Capable of conducting analysis, statistics, and data literacy to deduce where the challenges and opportunities lie.
#J-18808-Ljbffr
Principal Applied Research Machine Learning Engineer employer: PC Games Insider
Contact Detail:
PC Games Insider Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Applied Research Machine Learning Engineer
✨Tip Number 1
Familiarize yourself with the latest advancements in machine learning, especially those relevant to ad optimization. Follow key researchers and publications in the field to stay updated on innovative techniques that could be applied at Unity.
✨Tip Number 2
Engage with the Unity community through forums or social media platforms. This will not only help you understand the company culture but also allow you to network with current employees who can provide insights into the team dynamics and expectations.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully implemented machine learning solutions. Be ready to explain your thought process, the challenges you faced, and how your contributions led to measurable outcomes.
✨Tip Number 4
Demonstrate your ability to communicate complex machine learning concepts clearly. Practice explaining your work to non-technical audiences, as this skill is crucial for collaborating with product and engineering teams at Unity.
We think you need these skills to ace Principal Applied Research Machine Learning Engineer
Some tips for your application 🫡
Understand Unity's Values: Familiarize yourself with Unity's core values of Empathy, Respect, and Opportunity. Reflect these values in your application to show that you align with their culture.
Highlight Relevant Experience: Emphasize your experience in machine learning and data science, particularly any projects where you've successfully translated research into product innovations. Use specific examples to demonstrate your impact.
Showcase Technical Skills: Detail your expertise with modeling frameworks like TensorFlow or PyTorch. Include any relevant projects or research that showcase your understanding of model architectures and mechanisms.
Communicate Clearly: Ensure your application clearly communicates your ability to explain complex machine learning concepts. Use straightforward language to describe your analysis and how it can drive improvements in Unity's Ad platform.
How to prepare for a job interview at PC Games Insider
✨Showcase Your Research Experience
Be prepared to discuss your past research projects in detail. Highlight how you've successfully translated complex machine learning concepts into practical applications, especially those that had a significant impact on product innovation.
✨Demonstrate Technical Proficiency
Familiarize yourself with the latest machine learning frameworks like TensorFlow and PyTorch. Be ready to explain your experience with these tools and how you've utilized them to optimize models and algorithms in previous roles.
✨Communicate Clearly
Since you'll be working closely with product and engineering teams, practice explaining complex machine learning concepts in simple terms. This will demonstrate your ability to bridge the gap between technical and non-technical stakeholders.
✨Prepare for Hypothesis-Driven Discussions
Think about how you would approach forming and validating hypotheses related to machine learning. Be ready to discuss specific examples where you've analyzed data to identify challenges and opportunities, and how you drove optimization based on your findings.
