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Crunchyroll, LLC

Senior MLOps Engineer

Hyderabad · Staff/Principal

Older listing - lower visibility likelyVerified listingPosted 115d ago

Applicants who checked fit first are 3.1× more likely to hear back

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86Overall
64Skills
97Experience

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What we know about this role

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Crunchyroll, LLC is actively reviewing profiles and moving candidates through the pipeline right now.

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Window passed - posted 115d ago

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Skills required

18 listed
Large Language Models (LLMs)CI/CDAWS SageMakerMachine LearningTrend AnalysisJoint VenturesMLOps (Machine Learning Operations)MLflow+10 more
Large Language Models (LLMs)CI/CDAWS SageMakerMachine LearningTrend Analysis

You almost certainly match several of these already. Unlock your skill map to see the matches, the gaps, and what to fix first.

Job description

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

Crunchyroll is growing and changing, presenting unique challenges and opportunities to support millions of anime fans around the world. The AI/ML team provides seamless help to our internal stakeholders, ensuring an exceptional experience for all Crunchyroll fans. The AI/ML team relies on strong MLOps practices to ensure models are reliable, scalable, and impactful in production.

  • Design, build, and maintain end-to-end ML infrastructure and pipelines to support model training, deployment, and monitoring.
  • Develop and manage CI/CD pipelines for ML to enable fast, reliable, and automated delivery of ML models.
  • Implement and manage model registry, experiment tracking, and versioning using tools like MLflow, SageMaker Model Registry, or equivalent.
  • Establish monitoring, observability, and alerting frameworks to detect drift, degradation, and anomalies in real-time.
  • Partner with data scientists to productionize ML models, ensuring seamless transition from research to production.
  • Optimize ML workflows for performance, scalability, and cost-effectiveness across training and inference.
  • Leverage platforms such as AWS SageMaker, Databricks, Kinesis, Lambda, Kubernetes (EKS), and Docker for ML operations.
  • Collaborate with data engineering and software engineering teams to integrate ML services into large-scale distributed systems.
  • Drive best practices for MLOps, including reproducibility, governance, compliance, and security of deployed models.

How you’ll work with Data Science

  • Partner with ML Engineers to deploy and scale models built with frameworks like PyTorch, TensorFlow, and Scikit-learn.
  • Help data scientists track experiments, compare runs, and promote models to production.
  • Translate research notebooks into production-grade pipelines with reproducible training and inference workflows.
  • Co-own model lifecycle management: data, training, validation, deployment, monitoring, retraining.
  • Ensure ML models align with software engineering best practices for testing, automation, and observability.

About You

We get excited about candidates, like you, because...

  • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
  • 8+ years of experience in MLOps, ML infrastructure, or DevOps for AI/ML systems.
  • MLflow, SageMaker, Databricks ML for experiment tracking, model registry, and lifecycle management.
  • Airflow, or Step Functions for workflow orchestration.
  • MLFLow for monitoring ML models in production.
  • Deep knowledge of CI/CD and automation frameworks (GitHub Actions, Terraform, CloudFormation).
  • Hands-on experience with containerization (Docker) and orchestration (EKS).
  • Proficiency in Python and scripting for ML integrations.
  • Strong knowledge of cloud platforms (AWS preferred) and services relevant to ML (SageMaker, Lambda, S3, Kinesis, Step Functions).
  • Understanding of security, compliance, and governance in ML production systems.
  • Excellent problem-solving and communication skills, with a proven ability to work with cross-functional teams of data scientists

About the Team

The R&D team is dedicated to developing, testing, and validating robust and scalable machine learning models that drive business objectives. Our focus includes enhancing operational processes through AI/ML solutions, such as trend analysis, anomaly detection, and the deployment of large language models (LLMs) for tasks like querying system health. Another major focus area is preserving, and improving customer experience and retention. We closely work with our stakeholders to ensure AI/ML objectives are clearly defined.

Why you will love working at Crunchyroll

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

  • Best-in class medical, dental, and vision private insurance healthcare coverage
  • Access to counseling & mental health sessions 24/7 through our Employee Assistance Program (EAP)
  • Free premium access to Crunchyroll
  • Professional Development
  • Company's Paid Parental Leave
  • up to 26 weeks for birthing parents
  • up to 12 weeks for non-birthing parents
  • Hybrid Work Schedule
  • Paid Time Off
  • Flex Time Off
  • 5 Yasumi Days
  • Half-Day Fridays during the summer
  • Winter Break

#LifeAtCrunchyroll ((select from the following job modalities for this role: #LI-Hybrid #LI-remote #LI-onsite))

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.

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Two ways in

Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreCalculated · locked
86Overall
64Skills
97Experience

Your score for this role already exists

ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

No credit card · 1 tap with Google

Free · no signup

Get tomorrow's jobs before you have to search

Daily job drops, skill trends and free resources - posted straight to the group. Leave any time.

Join WhatsAppJoin Telegram

No spam. Just jobs and resources.

Why people use ASAI

Someone shared one job with you. ASAI keeps finding the rest.

  • Scored, not searched. Every role ranked against your actual profile.

  • Alerts as often as hourly. Reach new roles while the pile is still small.

  • Skill gaps, spelled out. See exactly which requirements you don't meet yet.

  • Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

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