At a Glance
- Tasks: Design and deploy cutting-edge machine learning systems for smarter media experiences.
- Company: Join Roku's Advanced Development team, a hub of innovation and creativity.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative culture that values creativity, trust, and ownership.
- Why this job: Make a real impact on how millions experience content through advanced technology.
- Qualifications: Master’s or PhD in Computer Science or related field with strong ML background.
The predicted salary is between 70000 - 90000 £ per year.
About the Team
The Advanced Development team at Roku pushes beyond today’s product lines to invent the next generation of intelligent and generative media systems. We explore ideas that sit years ahead of production, developing foundational technologies that will redefine how content is understood, created, and personalised across millions of Roku devices. This is a rare environment — a PhD-level, cross-disciplinary group combining machine learning research, software engineering, and DevOps. Everyone here is an expert, but not narrowly focused. The team blends deep technical mastery with broad creative vision — people who challenge convention, embrace ambiguity, and build what’s never been built before. It’s a collaborative, low-ego, ownership-driven culture built on trust and curiosity.
We’re seeking an Applied Scientist with a strong foundation in mathematics, machine learning, and computer science, combined with experience in cloud engineering, DevOps, and computer vision — someone who thrives where research meets production.
About the Role
As a Senior Applied Machine Learning Engineer, you’ll help design, build, and deploy the systems that make media smarter. You’ll work across the full model and software lifecycle, from prototype to production, developing scalable ML pipelines and cloud architectures that power generative AI, intelligent media understanding, content analysis, and advertising intelligence. You’ll operate at the intersection of machine learning, infrastructure, and software engineering, taking ownership from data collection through deployment — and seeing your work directly influence how audiences experience Roku’s content and advertising ecosystem.
What You’ll Be Doing
- Deploying scalable, fault-tolerant computer vision, media understanding, and generative AI systems to production
- Overseeing the full model development cycle: ideation, prototyping, implementation, deployment, testing, and operations
- Designing uncertainty metrics and communicating results to both technical and non-technical stakeholders
- Gathering and compiling datasets, defining annotation ontologies, auditing annotation operations, and ensuring data quality
- Staying up to date with industry and academic trends in computer vision, machine learning, and generative models for media and advertising
- Working closely with product and other engineering teams to implement new content and advertising experiences through cloud services
- Integrating services from other teams around the company, while also providing reusable ML services to others
- Evaluating and providing feedback on new platform technologies provided by internal teams
- Working with QA teams to address bugs and contribute to automation and quality assurance
We’re Excited If You Have
- A Master’s degree (PhD preferred) in Computer Science, Applied Mathematics, or a related field
- Strong background developing applied machine learning systems using PyTorch or TensorFlow
- Expertise in image processing, computer vision, or natural language processing
- Experience using AWS, GCP, or Azure for storing data, training, and serving models
- Proven ability to evaluate models and communicate insights effectively
- Experience building APIs with frameworks such as GraphQL or REST
- Experience with workflow orchestration tools such as Airflow, Argo, AWS Step Functions, or Metaflow
- Hands‑on experience with Docker, Kubernetes, Terraform, CloudFormation, CI/CD automation, and Python build or packaging tools
Senior Machine Learning Engineer in Cambridge employer: Gravity Engineering Services Pvt Ltd.
Roku is an exceptional employer for Senior Machine Learning Engineers, offering a unique opportunity to work within a pioneering Advanced Development team that thrives on innovation and collaboration. With a culture rooted in trust and curiosity, employees are encouraged to take ownership of their projects while benefiting from continuous learning and growth opportunities in a cutting-edge environment. Located at the forefront of media technology, Roku provides a stimulating atmosphere where your contributions directly shape the future of intelligent media systems.
Contact Details:
Gravity Engineering Services Pvt Ltd. Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Roku or similar companies. Attend meetups, webinars, or conferences where you can chat with potential colleagues and get the inside scoop on what they’re looking for.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving computer vision or generative AI. This is your chance to demonstrate your expertise and creativity, so make it shine!
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and ML concepts. Practice common algorithms and data structures, and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Machine Learning Engineer in Cambridge
Some tips for your application 🫡
Show Your Passion for Innovation:When writing your application, let us see your enthusiasm for pushing boundaries in machine learning and media systems. Share examples of how you've challenged conventions or embraced ambiguity in your past projects.
Highlight Your Technical Mastery:Make sure to showcase your expertise in applied machine learning, cloud engineering, and computer vision. Use specific examples that demonstrate your experience with tools like PyTorch, TensorFlow, and AWS to give us a clear picture of your skills.
Communicate Clearly:Remember, we value effective communication! Whether you're discussing technical concepts or project outcomes, make sure your application is easy to read and understand. Tailor your language to resonate with both technical and non-technical audiences.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to join our innovative team!
How to prepare for a job interview at Gravity Engineering Services Pvt Ltd.
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals, especially in areas like computer vision and generative AI. Be ready to discuss your experience with frameworks like PyTorch or TensorFlow, and have examples of projects where you've applied these skills.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled complex problems in previous roles. Think of specific instances where you designed scalable ML pipelines or deployed systems to production. Highlight your thought process and the impact of your solutions.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining your work in simple terms. Be ready to discuss how you gather and compile datasets, and how you ensure data quality without getting too bogged down in jargon.
✨Stay Current
Keep yourself updated on the latest trends in machine learning and computer vision. Mention any recent research or technologies that excite you during the interview. This shows your passion for the field and your commitment to continuous learning.
