Senior Machine Learning Engineer

Reposted 7 Days Ago
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Hyderabad, Telangana, IND
Hybrid
Senior level
Digital Media • eCommerce • Gaming • Mobile • News + Entertainment
The world’s largest destination for all things anime.
The Role
As a Senior Machine Learning Engineer, you'll design and deploy ML systems for user personalization, lead projects, optimize data pipelines, and enhance product engagement, while mentoring junior engineers.
Summary Generated by Built In
About Crunchyroll

Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We super-serve over 100 million anime and manga fans across 200+ countries and territories, and help them connect with the stories and characters they crave. Whether that experience is online or in-person, streaming video, theatrical, games, merchandise, events and more, it’s powered by the anime content we all love.

Join our team, and help us shape the future of anime!

About the role

We are seeking a Senior Machine Learning Engineer in the Hyderabad area to design, build, and scale machine learning systems that power personalized and data-driven experiences across our digital entertainment ecosystem — including paid VOD streaming, Manga reading, Merchandising, Mobile Gaming, and Music Video platforms. The role will be reporting to the Manager of Machine Learning.

You will work at the intersection of user behavior, content intelligence, and product engagement, building models and systems that both enhance user experience (e.g., personalization, discovery, lifecycle optimization) and generate actionable business insights and services for internal stakeholders. As a senior individual contributor, you will own high-impact initiatives end-to-end and play a key role in shaping the technical direction of ML systems across products.

Core Areas of Responsibility
  • Design, develop, and deploy scalable machine learning models that enhance personalization, discovery, engagement, and monetization across multiple product verticals.
  • Lead end-to-end ML projects from problem framing and data exploration to production deployment and monitoring.
  • Build and optimize robust data pipelines and feature engineering workflows for large-scale behavioral and content data.
  • Design and execute rigorous experimentation frameworks (e.g., A/B testing, offline evaluation) to measure model impact.
  • Collaborate closely with Product, Engineering, Analytics, and business stakeholders to translate product goals into ML solutions.
  • Improve system reliability, scalability, and performance of production ML services.
  • Mentor junior engineers and contribute to raising the team’s technical standards and best practices.
  • Contribute to the evolution of ML architecture, tooling, and MLOps practices across the organization.
About YouRequired Qualifications
  • 8+ years of experience building and deploying machine learning systems in production environments
  • Strong foundation in machine learning algorithms, statistics, and model evaluation techniques
  • Experience working with large-scale user behavior or content datasets
  • Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, xgboost)
  • Experience with distributed data processing and data pipeline technologies
  • Strong understanding of experimentation methodologies and performance measurement
  • Ability to operate independently and drive ambiguous problems to impactful solutions
Preferred Qualifications
  • Experience with recommendation systems, ranking models, personalization, or user lifecycle modeling
  • Experience in subscription-based digital products, streaming media, gaming, or e-commerce platforms
  • Familiarity with cloud infrastructure and production ML services
  • Experience optimizing models for real-time or near real-time user-facing applications
What Success Looks Like
  • ML systems you build measurably improve user engagement, retention, or monetization
  • Models are reliable, scalable, and well-integrated into product workflows
  • Stakeholders trust your technical judgment and rely on your work to inform product direction
  • You elevate the team’s engineering rigor and contribute meaningfully to long-term ML platform evolution
About the Team

You will join a fast growing team of Data Scientists, Machine Learning Engineers, and AI Engineers, united by a passion for leveraging data and AI to create transformative solutions. Our team delivers both consumer-facing product features that enhance the streaming experience for millions of users and stakeholder-oriented solutions that empower internal teams with actionable insights. From building personalized recommendation systems to developing innovative tools like our stakeholder-facing chatbot, we combine cutting-edge machine learning, robust data pipelines, and advanced AI to drive impact across the organization. Collaboration, creativity, and a commitment to excellence define our team’s culture as we work together to push the boundaries of what’s possible in streaming and data-driven decision-making.

About our Values

We want to be everything for someone rather than something for everyone and we do this by living and modeling our values in all that we do. We value

  • Courage. We believe that when we overcome fear, we enable our best selves.

  • Curiosity. We are curious, which is the gateway to empathy, inclusion, and understanding.

  • Kaizen. We have a growth mindset committed to constant forward progress.
  • Service. We serve our community with humility, enabling joy and belonging for others.

Our commitment to diversity and inclusion

Our mission of helping people belong reflects our commitment to diversity & inclusion. It's just the way we do business.

We are an equal opportunity employer and value diversity at Crunchyroll. Pursuant to applicable law, we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Crunchyroll, LLC is an independently operated joint venture between US-based Sony Pictures Entertainment, and Japan's Aniplex, a subsidiary of Sony Music Entertainment (Japan) Inc., both subsidiaries of Tokyo-based Sony Group Corporation.

Questions about Crunchyroll’s hiring process? Please check out our Hiring FAQs: https://help.crunchyroll.com/hc/en-us/articles/360040471712-Crunchyroll-Hiring-FAQs

Please refer to our Candidate Privacy Policy for more information about how we process your personal information, and your data protection rights: https://tbcdn.talentbrew.com/company/22978/v1_0/docs/spe-jobs-privacy-policy-update-for-crpa-dec-21-22.pdf

Please beware of recent scams to online job seekers. Those applying to our job openings will only be contacted directly from @crunchyroll.com email account.

What the Team is Saying

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The Company
Berlin, Germany
1,300 Employees
Year Founded: 2006

What We Do

At Crunchyroll, we deliver what anime fans love—anytime, anywhere. With the world’s largest anime streaming library, we connect fans to the stories, characters, and creators they love. But Crunchyroll is more than just a destination to watch anime—it's a global ecosystem where anime lives and breathes beyond the screen. From streaming and theatrical releases to merch, games, news, events, and music, we offer fans immersive experiences that celebrate anime culture in all its forms. Headquartered in the U.S. with teams and reach across the globe, Crunchyroll is an independently operated joint venture between Sony Pictures Entertainment and Aniplex of Japan. This unique partnership gives us the power to scale globally while staying rooted in anime’s cultural origins, ensuring authenticity and access for fans everywhere. We believe anime is more than entertainment—it’s a way of life. And we’re here to champion that passion every day.

Why Work With Us

We take the People Experience seriously here at Crunchyroll. Join a diverse team of talented, ambitious people who treat each other well and believe that how we win is just as important as winning.

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Crunchyroll Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Three in-person days per week. Tuesdays, Wednesdays, and Thursdays are the company-wide days for ALL team members to be in the office, and individuals may choose to come in more if they please.

Typical time on-site: 3 days a week
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