At a Glance
- Tasks: Build and enhance machine learning systems for marketing and advertising.
- Company: Join Roku, the leading TV streaming platform revolutionising how the world watches TV.
- Benefits: Enjoy competitive pay, mental health support, flexible work options, and comprehensive benefits.
- Other info: Collaborative hybrid work environment with excellent career growth opportunities.
- Why this job: Make a real impact in the fast-paced world of TV streaming and advertising technology.
- Qualifications: Strong background in machine learning, coding skills, and experience with data analysis.
The predicted salary is between 60000 - 80000 £ per year.
Teamwork makes the stream work. Roku is changing how the world watches TV. Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.
About the Team: Roku pioneered TV streaming and continues to innovate and lead the industry. The Roku Channel has us well-positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them. Within Advertising Engineering, the MarTech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience to the right customer at the right time on the right marketing channel. The team is focused on turning data, experimentation, and intelligent decisioning into production systems that improve marketing effectiveness at scale. Our mission is to build cutting‑edge advertising technology and marketing products to support and grow a sustainable advertising business. The team owns server technologies, data platforms, and cloud services that power advertising and marketing use cases.
We are recruiting a Senior Machine Learning Engineer to build and enhance intelligent systems that help the marketing team harness the power of data.
About the Role: The MarTech team at Roku is looking for a seasoned Senior Machine Learning Engineer with a strong background in machine learning and production systems. This role sits in a team working on high-impact problems across marketing and advertising, where machine learning is being applied to improve customer decisioning, creative and campaign performance, and the systems that support experimentation and optimisation. Examples of such problems include creative personalisation for customers, improving ad relevance and targeting, inferring demographics, yield optimisation, and many more. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, recommendations, reinforcement learning, optimisation, probability theory, and machine learning, using code for statistical analysis and tool building, using both general-purpose software and statistical languages.
The ideal candidate will have endless curiosity and can pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can work effectively with engineering, product, data science, and commercial stakeholders across Roku. The successful candidate will display a balance of hard and soft skills, including the ability to respond quickly to changing business needs. This role requires hybrid working from the Roku Manchester office.
What You'll Be Doing:
- Data Analysis / Feature Engineering: Apply your expertise to identify and calculate features that can be leveraged by multiple use cases as well as models.
- Train Machine Learning Models: Use machine learning and statistical modelling techniques such as recommendations, reinforcement learning, decision trees, Bayesian analysis, neural networks and transformers to develop and evaluate algorithms to address business use cases and/or to improve product/system performance, quality and accuracy.
- Near Real-Time and Batch Inferencing: Use infrastructure like Spark and Ray to stand up inferencing services that integrate with operational/analytics workloads.
- ML Infrastructure: Help build a first-class machine learning platform from the ground up which helps manage the entire model lifecycle: feature engineering, model training/evaluation, versioning, deployment/online serving and monitoring prediction quality.
- Low-Level Systems Debugging, Performance Measurement & Optimisation: Performance measurement and optimisation on large production clusters.
We're Excited If You Have:
- First-hand experience in applied machine learning on real recommendations use cases (brownie points for productionised sequential learning use cases!).
- Experience with ML/distributed ML frameworks like Ray, Spark-MLlib, TensorFlow etc.
- Experience with real-time scoring/evaluation of models with low latency constraints.
- Great coding skills and strong software development experience (we use Spark, Python and Java a lot).
- Ability to work with large-scale computing frameworks, data analysis systems and modelling environments. Examples include technologies like Spark, Hive, NoSQL stores etc.
- Bachelor’s, Master’s or PhD in Computer Science, Statistics or a related field.
- Ad‑tech/Mar‑tech background is a plus.
Our Hybrid Work Approach: Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five day in office policy.
Benefits: Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It’s important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.
Accommodations: Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.
Senior Software Engineer, Machine Learning in Manchester employer: Roku, Inc.
Roku is an exceptional employer that champions innovation and collaboration, making it a thrilling place for a Senior Software Engineer in Machine Learning. With a strong commitment to employee growth, a diverse range of benefits, and a hybrid work culture that promotes work-life balance, Roku empowers its team members to make impactful contributions while enjoying the flexibility of remote work on Fridays. Located in Manchester, employees benefit from a vibrant tech community and the opportunity to work on cutting-edge advertising technology that shapes the future of streaming.
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We think this is how you could land Senior Software Engineer, Machine Learning in Manchester
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We think you need these skills to ace Senior Software Engineer, Machine Learning in Manchester
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Roku, Inc..
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Roku, Inc. and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Roku, Inc.
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Roku, Inc. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.