About the role

As a Staff Data Analyst, you will lead high-impact analytical work that shapes Crunchyroll’s content strategy - from greenlight to presentation to engagement and retention. You’ll define measurement frameworks, build certified data assets, and partner closely with Content Strategy, Programming, Product, and Licensor teams to deliver insights that guide multi-million-dollar decisions. This role operates with broad autonomy and plays a key part in raising analytical rigor, strengthening data quality, and establishing standards across the Fan Experience (FX) Team.

You will:

• Lead content measurement frameworks: define north-star KPIs, normalization methods, and comparable title metrics to drive consistent decision-making across regions, seasons, modalities, and content types.
• Build certified, reusable data assets: develop durable datasets in Databricks that standardize title/season/episode joins and metadata keys, ensuring high-quality, consistent downstream analysis.
• Advance understanding of content impact: quantify title-driven acquisition, engagement, and retention; model content-attributed churn risk; and develop portfolio-level diagnostics to inform slate and localization decisions.
• Own and evolve attribution & user-journey insights: maintain and improve viewership attribution logic to map discovery → click → watch → return behaviors, enabling clear readouts on how users discover and engage with titles.
• Drive experimentation and presentation measurement: design success metrics, partner on eventing, and analyze experiments for homepage rails, thumbnails, recommendations, language selectors, and other discovery/presentation surfaces.
• Deliver decision assets for Content & Licensors: produce clear analyses, dashboards, and reusable frameworks for greenlight, localization ROI, curation, licensor narratives, and internal/external self-serve tooling.
• Elevate analytics craft & standards: document methods, set QA and analysis standards, mentor analysts across VODAX, and support hiring to strengthen long-term analytics capability.

In the role of Staff Data Analyst, Content Analytics, you will report to the Manager, Content Analytics. We are considering applicants for Los Angeles (in office Tuesdays, Wednesdays, and Thursdays).

About You

We get excited about candidates, like you, because…

• You have 12+ years of experience in content, product, or streaming analytics with a track record of solving highly complex, ambiguous problems that influence org-level decisions.
• You possess expert SQL and strong Python/PySpark skills, with hands-on experience working in Databricks or similar lakehouse environments.
• You have deep experience with large-scale viewership, subscription, or payments datasets and have built certified datasets or BI-ready data assets.
• You possess strong experimentation and causal inference skills including test design, metric definition, and analysis of A/B results.
• You have fluency with Tableau or similar BI tools and can design dashboards that scale across stakeholder groups.
• You embody domain expertise in streaming/content analytics including attribution modeling, content normalization, and understanding how content impacts user behavior and retention.

About the Team

You will join the Fan Experience (FX) team within the Center for Data & Insights (CDI) organization with a focus on Content Analytics. The team builds core engagement metrics, attribution logic, experimentation frameworks, and licensor-facing insights that support decision-making across the content lifecycle - from greenlight to discovery to retention. As Crunchyroll continues to scale globally, the team is expanding its capabilities and establishing durable measurement foundations that support partners across Content, Product, and the broader CDI organization.

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:

• Receive a great compensation package including salary plus performance bonus earning potential, paid annually.
• Flexible time off policies allowing you to take the time you need to be your whole self.
• Generous medical, dental, vision, STD, LTD, and life insurance
• Health Saving Account HSA program
• Health care and dependent care FSA
• 401(k) plan, with employer match
• Employer paid commuter benefit
• Support program for new parents
• Pet insurance and some of our offices are pet friendly!

#LifeAtCrunchyroll #LI-Hybrid

About the role

In the role of senior machine learning engineer, you will report to the director of data science and machine learning in the Center for Data and Insights, working from Los Angeles or San Francisco area in California.

In this Machine Learning Engineer role focused on Algorithm Development and End-to-End Production at our VOD streaming company, you will lead the creation and deployment of scalable ML models to detect account sharing fraud, drawing from user behavior data like geolocation, concurrent sessions, and device profiles. This position is essential for collaborating with data scientists, product analysts, and data engineers,  translating research prototypes into production systems that enhance detection accuracy while minimizing user disruption, aligning with proven strategies from streaming giants to boost subscriber growth.

We work a hybrid schedule, in-office three days a week; Tuesday, Wednesday, Thursday. 

Core Areas of Responsibility

• Design and implement machine learning algorithms, including anomaly detection models, to identify unauthorized account sharing in real-time.
• Develop end-to-end ML pipelines for data preprocessing, model training, evaluation, and deployment using cloud platforms.
• Optimize models for performance, scalability, and efficiency to handle high-volume streaming data.
• Integrate ML solutions with existing systems via APIs and establish monitoring for model drift and retraining.
• Collaborate on A/B testing and iteration to refine algorithms based on feedback and evolving evasion tactics.

About You

• Experience: You bring 5+ years of hands-on experience in ML engineering, with a track record in fraud or anomaly detection systems, ideally in online, consumer facing products and services.
• Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or XGBoost, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks MLFlow, etc. Experience with cloud computing infra and tooling such as AWS/GCP.
• Cross-Functional Collaborations: Experienced in working with data scientists, engineers, and product teams to deploy models that support business goals like revenue optimization.
• Communication Skills: Strong ability to document technical processes and explain algorithm decisions to diverse stakeholders for seamless integration.
• Education Background: Possess a master's degree in computer science, machine learning, or a related quantitative field, with certifications in cloud ML being a plus.
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Educational Background: Graduate degree (MS or PhD) in Computer Science, Statistics, or a related field.

About the Team

Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.

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:

#LifeAtCrunchyroll #LI-Hybrid

About the role

In the role of Senior Machine Learning Engineer for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in the Center for Data and Insights, working from Los Angeles or San Francisco area in California. You will lead the research, development, and test of advanced models, and work together with product and engineering partners to deliver tailored experiences for our fans across the anime ecosystem, including anime video recommendations, digital manga suggestions, merchandise personalization, anime-themed gaming, music, and more. This position will collaborate closely with scientists, engineers, product owners, to prototype innovative algorithms, evaluate their impact, and integrate them into production systems that drive user engagement, retention, discovery, and satisfaction.

We work a hybrid schedule, in-office three days a week; Tuesday, Wednesday, Thursday. This position can be based in our Los Angeles or San Francisco offices.

Core Areas of Responsibility

• Research, design, and implement machine learning algorithms for recommendation systems, including collaborative filtering, content-based models, and deep learning, and generative recommendation approaches to personalize content discoveries.
• Co-develop end-to-end ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment using scalable cloud platforms with engineers.
• Optimize models for accuracy, latency, and scalability to handle massive user interaction data from streaming and multi-platform, multi-domain experiences across the fandom.
• Integrate personalization solutions with other services, and implement monitoring for model performance, bias detection, and automated retraining.
• Collaborate on A/B testing, experimentation, and iterative improvements to refine recommendations based on user feedback and evolving content trends.

About You

We get excited about candidates, like you, because you have:

Experience: You bring 8+ years of hands-on experience in applied machine learning, with a proven track record in building recommendation systems or personalization engines, ideally in media, entertainment, or e-commerce platforms.

Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or Scikit-learn, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks, or similar. Experience with big data tools (e.g., Spark) and cloud infrastructure (e.g., AWS/GCP) for handling large-scale datasets.

Cross-Functional Collaborations: Experienced in partnering with data scientists and analysts, engineers, and product teams to deploy models that align with business objectives like increasing user retention and content consumption.

Communication Skills: Strong ability to document research findings, explain algorithmic choices, and present results to diverse stakeholders for effective adoption.

Educational Background: Graduate degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related quantitative field, with publications or contributions in recommendation systems being a plus.

About the Team

Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.

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:

#LifeAtCrunchyroll #LI-Hybrid

About the role

In the role of Data Scientist, you will report to the Director of Machine Learning and Data Science. We are considering applicants for the location(s) of Los Angeles, CA or San Francisco.

We are seeking a Data Scientist with skills and experience in using User Behavior Analytics and Modeling to kick start our effort to detect and deter account sharing by leveraging platform-collected data such as login patterns, device usage, IP addresses, and viewing behaviors. This position focuses on uncovering insights from large datasets to inform machine learning models that identify anomalous sharing activities, ultimately supporting revenue growth and subscriber retention strategies inspired by industry leaders like Netflix and Disney+.

Core Areas of Responsibility

• Conduct exploratory data analysis on user session logs to establish baselines for normal and anomalous behaviors.
• Develop predictive models using statistical and machine learning techniques to forecast and segment user sharing patterns.
• Design and conduct experiments to validate the model accuracy and operations effectiveness.
• Collaborate with cross-functional teams to define data requirements and create frameworks for ongoing behavioral monitoring.
• Build visualizations and reports to communicate insights on user engagement and potential sharing risks to stakeholders.
• Ensure data privacy compliance while optimizing data pipelines for efficient operations.

About You

We get excited about candidates, like you, because you have the following:

• Experience: You have 5+ years in data science roles focused on behavioral analytics, preferably in tech or streaming industries, with proven success in user behavior modeling, anomaly and fraud detection, and related applications.
• Technical Skills: Proficient in Python for data analysis and modeling, SQL for database querying, and tools like Tableau or matplotlib for visualization, with experience in machine learning libraries such as xgboost, scikit-learn, and pytorch for modeling.
• Cross-Functional Collaborations: Skilled at partnering with engineering, product, and legal teams to align analytics with business objectives and integrate findings into product features.
• Communication Skills: Adept at presenting complex behavioral insights in clear, actionable formats to non-technical audiences through reports and visualizations.

Education Background: Hold a master's degree in data science, statistics, computer science, or a related field, with coursework in behavioral economics or psychology being advantageous.

About the Team

You will join an interdisciplinary team of Data Scientists, Machine Learning Engineers, and AI Engineers, united by a passion for leveraging data and ML/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.

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:

#LifeAtCrunchyroll #LI-Hybrid

About the role

We are looking for a Manager, Machine Learning and Data Science in the Hyderabad Area to lead and scale a team applying advanced Data Science and Machine Learning to a global digital entertainment platform. Our ecosystem spans paid VOD streaming, online Manga reading, Merchandising, Gaming, and Music Video experiences, all centered on deep user engagement and premium content consumption regarding the anime fandom.

In this role, you will manage a team of Machine Learning and AI Engineers, and Data Scientists focused on understanding content, user behavior, and product engagement, and turning those insights into actionable business insights and product features that offer personalized user experiences. You will partner closely with the Director of Data Science & Machine Learning (DSML) to scale both the team and the technical capabilities needed to support a growing, multi-product platform.

This role is ideal for a leader who combines strong technical judgment with people leadership, and who can guide teams from exploratory analysis to production-ready ML systems that directly impact customer experience and business outcomes.

Core Areas of Responsibility

• Lead, mentor, and develop a team of Machine Learning Engineers and Data Scientists, fostering a culture of technical excellence and accountability.
• Drive delivery of ML and analytics initiatives that enhance content discovery, personalization, user engagement, and cross-platform experiences.
• Provide technical oversight on modeling approaches, experimentation, and production readiness to ensure scalable and reliable solutions.
• Translate business objectives into clear ML roadmaps in partnership with Product, Engineering, and business stakeholders.
• Ensure insights and model outputs are effectively communicated to inform strategic and operational decisions.
• Establish and standardize best practices across experimentation, evaluation, deployment, and monitoring of ML systems.
• Identify opportunities to leverage data and ML across streaming, manga, gaming, merchandising, and music verticals.
• Partner with the Director of DSML to scale team capabilities, processes, and long-term technical strategy.

About You

Required Qualifications

• 5+ years of experience in Data Science, Machine Learning, or Applied Analytics
• 2+ years of experience leading or managing technical teams
• Strong understanding of ML systems applied to user behavior, content, or product analytics
• Experience delivering ML solutions that inform business decisions and/or power user-facing features
• Ability to guide technical design and evaluate trade-offs without being hands-on day-to-day
• Strong communication skills and comfort working with product and business stakeholders

Preferred Qualifications

• Experience in subscription-based digital products, media, streaming, gaming, or e-commerce
• Experience with personalization, recommendations, or engagement optimization
• Familiarity with ML platforms, data pipelines, and production ML workflows at scale
• Experience operating in a multi-product or platform environment and cross-timezone collaborations.
  
  

What Success Looks Like

• The team consistently delivers ML-driven insights and experiences that improve user engagement and satisfaction
• Personalized content and service offerings become more effective, measurable, and scalable

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.

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))

We are hiring an Applied Scientist to help advance personalization across the Crunchyroll ecosystem. In this role, you will lead the scientific development of recommendation, ranking, and decisioning solutions that improve how fans discover and engage with anime series/movies, manga, merchandise, games, and other areas in the anime fandom. You will partner closely with Machine Learning Engineers, Product, Engineering, Marketing, and Content stakeholders to make Crunchyroll the ultimate destination for anime experience.

About the role

In the role of Senior Applied Scientist for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in our Center for Data and Insights. You will own the research and applied science agenda for personalization, from problem framing and data exploration through model development, evaluation, experimentation, and iteration. This role is ideal for someone who enjoys combining strong scientific rigor with product thinking to improve user discovery, engagement, retention, and long-term fan value.

You will work across multiple user touchpoints, including app and web interfaces, lifecycle and promotional email campaigns, and flywheels that connect video, ecommerce, manga, and adjacent experiences. You will help define what great personalization looks like at Crunchyroll, build the evidence to prove impact, and collaborate with engineering partners to ensure the resulting solutions can be productionized effectively.

This position is based in our Los Angeles office, but we will consider our San Francisco office as a secondary location. We work a hybrid schedule, in-office three days a week: Tuesday, Wednesday, and Thursday. 

Core areas of responsibility

• Lead the research and development of recommendation, ranking, retrieval, and personalization methods tailored to Crunchyroll use cases across streaming, manga, ecommerce, and lifecycle marketing surfaces.
• Frame ambiguous business and product questions into clear scientific problems, hypotheses, success metrics, and experimentation plans.
• Design and run robust offline evaluation frameworks for recommender systems, including relevance, diversity, novelty, coverage, calibration, and long-term value metrics.
• Partner with Product, Analytics, and Engineering to define online experiments, interpret results, and turn learnings into roadmap decisions and model improvements.
• Develop user, content, and contextual understanding through feature design, representation learning, segmentation, and behavioral analysis.
• Prototype and evaluate a range of approaches, including collaborative filtering, content-based methods, sequence modeling, deep learning, bandits, causal or uplift methods, and LLM-enabled recommendation techniques where appropriate.
• Analyze user feedback loops and cross-domain interactions to improve discovery across video, merchandise, manga, and other ecosystem experiences.
• Work closely with Machine Learning Engineers to translate promising research into production-ready solutions on our in-house recommendation platform.
• Communicate scientific findings, model tradeoffs, and business implications clearly to technical and non-technical stakeholders.
• Help establish best practices for experimentation, reproducibility, model governance, and scientific documentation within the personalization and recommendations function.

About you

We get excited about candidates, like you, because you have:

Experience: You bring 5+ years of experience in applied machine learning, recommendation systems, search/ranking, experimentation, or a closely related area, with a track record of driving measurable product impact.

Scientific Depth: You have strong foundations in machine learning, statistics, experimental design, and causal thinking, and you know how to choose the right level of modeling complexity for the problem at hand.

Recommendation Expertise: You have hands-on experience with at least some of the following: collaborative filtering, retrieval and ranking systems, representation learning, sequence / generative models, bandits, graph methods, or personalization for consumer products.

Technical Skills: You are highly proficient in Python and comfortable working with common ML libraries such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or similar tooling. Experience working with SQL, distributed data processing, and cloud-based ML workflows is strongly preferred.

Experimentation Mindset: You know how to design offline and online evaluations, reason carefully about metrics, and connect experimental findings to user and business outcomes.

Cross-Functional Collaboration: You have experience partnering effectively with engineers, product managers, analysts, marketers, and business stakeholders to move from idea to execution.

Communication Skills: You can explain sophisticated modeling decisions and ambiguous findings in a clear, decision-oriented way to diverse audiences.

Educational Background: You hold an MS or PhD in Computer Science, Machine Learning, Statistics, Operations Research, Economics, or a related quantitative discipline, or you bring equivalent applied industry experience.

Nice to have

• Experience personalizing content, commerce, media, entertainment, gaming, or subscription products at scale.
• Familiarity with recommender-system failure modes such as popularity bias, cold start, sparse feedback, and feedback loop effects.
• Experience with multi-objective optimization, constrained ranking, or balancing short-term engagement with long-term user value.
• Exposure to generative AI, representation learning, or LLM applications that support recommendation and personalization workflows.
• Published research, patents, or open-source contributions in recommendation systems, personalization, applied machine learning, or experimentation.

About the team

Our centralized DS/ML team serves stakeholders across Finance, Product, Engineering, Marketing, Creatives, and Content Operations with data-driven and ML/AI-powered solutions. Within that broader organization, the Personalization and Recommendation group is building the next generation capabilities to power tailored fan experiences across every major user interface and lifecycle touchpoint. Today, the team includes engineers focused on operationalizing our recommendation platform with strong engineering excellence. This Applied Scientist role complements that foundation by bringing deeper scientific ownership to modeling strategy, evaluation, and experimentation, while partnering closely with an additional MLE hire to accelerate production impact.

Why this role is exciting

• You will help define personalization strategy across multiple surfaces instead of optimizing a single narrow funnel.
• You will work on problems that span content discovery, user engagement, retention, and cross-domain ecosystem value.
• You will influence both what we build and how we measure success, with strong exposure to partners across the business.
• You will join at a formative moment, with the opportunity to shape team standards, technical direction, and long-term roadmap.

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:

#LifeAtCrunchyroll #LI-Hybrid

About the Role

We are seeking a Marketing Science Analyst II to join our Marketing Analytics team in Hyderabad. In this role, you will partner with paid media, growth, and cross-functional teams to measure and optimize marketing performance across digital and offline channels. You will play a key role in campaign measurement, attribution, experimentation, and reporting—translating complex data into actionable insights that drive business growth.

This position is ideal for a highly analytical professional with hands-on marketing analytics experience who is ready to take ownership of measurement frameworks while collaborating across a global organization.

Responsibilities

Campaign Measurement & Attribution

• Support the tracking and reporting of campaign performance by compiling relevant KPIs and spend data. 
• Assist in incrementality testing efforts and contribute to A/B test setup and execution for marketing initiatives. 
• Help evaluate performance using MMM inputs, basic channel lift analysis, and cross-channel measurement frameworks.

Performance Analytics & Optimization

• Track and report key performance metrics including Signups, CAC, CPFT, and payback periods.
• Conduct deep-dive analyses to identify performance drivers and optimization opportunities.
• Assist in maintaining regular campaign reporting across lines of business.
• Develop and refine audience segments for targeted paid campaigns, leveraging data insights to enhance performance

Data Analysis & Reporting

• Write complex SQL queries to analyze large datasets (millions to billions of records).
• Build and maintain dashboards in Tableau (or similar BI tools) to support stakeholder reporting needs
• Collaborate with analytics engineering teams to improve data quality, pipelines, and reporting processes.

Experimentation & Insights

• Assist in executing the test roadmap aligned with marketing goals.
• Apply basic statistical methods to evaluate experiments and measure performance impact.
• Support the translation of findings into clear insights and actionable recommendations.
• Support MMM modeling efforts within Marketing Science by contributing to data inputs and assisting in the interpretation of model outputs for marketing measurement

Cross-Functional Collaboration

• Work closely with PMUA, GTM, Analytics, and Data Engineering teams to align on KPIs and measurement standards.
• Maintain documentation and support alignment across teams.
• Contribute to bi-weekly insights decks and leadership reporting.

About You

• 2+ years of experience in marketing analytics, data analytics, or a related quantitative field.
• 2+ years of experience writing complex SQL queries and working with large datasets.
• Experience with marketing attribution, paid media analytics, and performance measurement.
• Familiarity with marketing tools such as Google Analytics, Braze,Singular, Mixpanel  or similar platforms.
• Strong understanding of:
• Descriptive statistics
• Experimental design and A/B testing
• Key marketing KPIs (CAC, LTV, ROAS, retention)
• Familiarity with statistical methods and exposure to data science techniques (e.g., regression, experimentation, MMM) in a marketing analytics context.
• Experience with BI tools such as Tableau, Power BI, or similar.
• Strong communication skills with the ability to translate complex data into clear, actionable insights.
• Proven ability to collaborate across cross-functional and global teams.
• Bachelor’s degree in Statistics, Computer Science, Engineering, or a related quantitative field.

Good to Have

• Experience with cloud data warehouses such as Snowflake or Redshift.
• Exposure to Marketing Mix Modeling (MMM) or advanced attribution modeling.
• Experience with analytics engineering tools such as Databricks.
• Exposure to automation of marketing reporting pipelines.

A Day in the Life

• Analyze campaign performance across paid social, search, display, and offline channels.
• Evaluate incrementality tests and provide recommendations on budget allocation.
• Build dashboards and automated reports to scale insights delivery.
• Partner with marketing leads to refine KPIs and measurement frameworks.
• Deliver insights to leadership through structured storytelling and data visualization.
• Contribute to sprint planning and collaborate with global stakeholders to drive high-impact analytics initiatives.

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 You

Required 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.