Join arenaflex's Innovation Team: Shape the Future of Content Discovery
Are you ready to revolutionize how millions of users discover content they love? arenaflex is seeking a talented and passionate Senior Machine Learning Engineer to join our dynamic team responsible for building cutting-edge recommendation and personalization systems that power our industry-leading streaming platforms. This is a unique opportunity to work at the intersection of artificial intelligence, user experience, and content strategy—helping shape the way audiences engage with entertainment across the globe.
At arenaflex, we believe that exceptional user experiences drive lasting connections. Our recommendation systems are the heartbeat of our streaming services, serving as intelligent guides that connect viewers with content tailored to their unique preferences. As a Senior Machine Learning Engineer on this team, you'll be instrumental in developing algorithms that not only predict what users want to watch next but also discover new favorites they didn't know they were looking for.
What You'll Do
As a key individual contributor within our Happy Recommendations team, you will own the end-to-end lifecycle of recommendation and personalization algorithm development. Your work will directly impact how tens of millions of users experience our streaming platforms daily. Here's what your role entails:
Algorithm Development & Innovation
- Design, develop, and implement state-of-the-art machine learning models for personalization, recommendation, and predictive systems using advanced AI techniques
- Lead research into innovative, cutting-edge methodologies that can be applied to content recommendations, continuously pushing the boundaries of what's possible
- Build and maintain algorithms deployed to production environments, serving as the subject matter expert in explaining methodologies to both technical and non-technical stakeholders
- Develop minimum viable products (MVPs) for new features and create scalable solutions that can be leveraged by production algorithms
Analysis & Optimization
- Conduct deep-dive analyses on application interactions and user profiles as they relate to algorithm output, driving improvements in key personalization metrics
- Perform rigorous testing and validation of models to ensure accuracy, fairness, and optimal performance
- Identify patterns in user behavior that inform algorithm enhancements and new feature development
- Monitor and optimize system performance to meet and exceed KPIs for various product areas
Collaboration & Leadership
- Work cross-functionally with Product, Design, and Engineering teams to align on requirements and manage stakeholder expectations
- Collaborate with data teams across the organization to improve data collection, experimentation frameworks, and analytical capabilities
- Identify and define new personalization opportunities that align with broader company objectives
- Contribute to the strategic roadmap for algorithmic work, guiding not only how to approach product demands for new recommendation features but also driving larger organizational goals in personalization
Best Practices & Documentation
- Maintain existing and establish new standards for algorithm development, testing, and deployment
- Create comprehensive documentation that enables knowledge sharing and team collaboration
- Mentor junior team members and foster a culture of continuous learning and innovation
- Set and meet deadlines for both internal and external-facing tools, such as offline evaluation instruments for pre-production algorithms
What We're Looking For
Required Qualifications
- Educational Background: Bachelor's degree in Advanced Mathematics, Statistics, Data Science, Computer Science, or a related quantitative field
- Professional Experience: 5+ years of analytical experience in machine learning and data science roles
- Technical Proficiency: Extensive experience developing AI models and performing data analysis using Python or R
- Coding Skills: Strong ability to write production-level, scalable code (Python, Scala, or similar languages)
- ML Engineering: 3+ years of experience developing algorithms for deployment to production systems
- AI Expertise: In-depth understanding of modern AI methodologies, including deep learning techniques, models, and their mathematical foundations
- NLP Knowledge: Deep understanding of natural language processing techniques and contextualized word embedding models
- Infrastructure Experience: Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and designing big data solutions using technologies like Databricks, S3, and Flash
- Data Visualization: Proficiency with data analysis and visualization tools such as Tableau, Looker, or similar platforms
- Statistical Foundation: Strong grasp of statistical concepts including hypothesis testing and regression analysis
- Problem-Solving: Ability to assess the complexity of machine learning problems and willingness to implement straightforward approaches for rapid, effective solutions when appropriate
- Communication: Excellent written and verbal communication skills, with the ability to explain how models are used and algorithms behave to both technical and non-technical audiences
Preferred Qualifications
- Advanced degree (MS or PhD) in Statistics, Mathematics, Computer Science, Social Sciences, or a related quantitative field
- Production experience developing content recommendation algorithms at scale
- Experience with graph-based models (such as node2vec)
- Experience building and deploying full-stack ML pipelines: data extraction, data mining, model training, feature engineering, testing, and deployment
- Familiarity with graph-based data workflows like Apache Airflow
- Experience designing big data solutions using technologies such as EMR, S3, Flash, Databricks
- Knowledge of metadata management, data lineage, and data governance principles
- Experience loading and querying cloud-hosted databases like Snowflake
- Familiarity with automated deployment, AWS infrastructure, Docker, or similar containerization technologies
Why arenaflex?
At arenaflex, we don't just stream content—we stream possibilities. Our team is comprised of innovators, dreamers, and doers who are passionate about transforming how the world experiences entertainment. We offer more than just a job; we offer a career where your contributions matter and your growth is nurtured.
Work-Life Balance & Flexibility
We understand that great work happens when you have the freedom to be your best self. Our remote-first culture allows you to work from anywhere, giving you the flexibility to design your ideal work environment while collaborating with talented colleagues across the globe.
Professional Development
Learning is at the core of who we are. You'll have access to cutting-edge resources, conference opportunities, and ongoing training to stay at the forefront of AI and machine learning innovation. We invest in your growth because your advancement drives our success.
Competitive Compensation
We value your expertise and dedication. arenaflex offers competitive salaries, equity opportunities, and comprehensive benefits packages that include health, dental, and vision coverage, retirement plans, and generous paid time off.
Inclusive Culture
Diversity fuels our creativity. We're committed to building an inclusive environment where every voice matters, every perspective is valued, and diverse teams can thrive together. We believe that the best ideas emerge when different minds come together.
Ready to Make Your Mark?
If you're excited about the opportunity to work on complex algorithmic challenges that impact millions of users daily, if you're passionate about leveraging AI to create meaningful content experiences, and if you're ready to join a team that values innovation, collaboration, and excellence, then we want to hear from you.
At arenaflex, your next great opportunity is waiting. Apply today and help us shape the future of content discovery.
arenaflex is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.