Senior AI‑Driven Recommendation & Personalization Engineer – Real‑Time Video Streaming & Content Discovery (Remote, $25/hr)

About arenaflex – Shaping the Future of Entertainment

arenaflex is a global leader in streaming entertainment, delivering immersive, on‑demand video experiences to millions of households worldwide. With a portfolio that spans blockbuster movies, original series, and a growing library of exclusive content, arenaflex is redefining how audiences discover and engage with stories. Our commitment to innovation, data‑driven creativity, and a culture of continuous learning makes arenaflex the ideal place for visionary technologists who want to leave a lasting imprint on the entertainment industry.

Why This Role Matters

As a Senior AI‑Driven Recommendation & Personalization Engineer, you will be at the heart of arenaflex’s mission to deliver the right content to the right viewer at the right moment. You will partner with Product, Design, and Data teams to build cutting‑edge recommendation algorithms, develop scalable AI pipelines, and translate complex data insights into intuitive user experiences. Your work will directly influence key performance indicators such as watch time, user retention, and overall satisfaction, driving both business growth and creative excellence.

Key Responsibilities

• Algorithm Design & Development: Lead the end‑to‑end design, implementation, and optimization of recommendation and personalization models that power arenaflex’s real‑time video applications.
• Cross‑Functional Collaboration: Work closely with Product Managers, UX Designers, and Engineering teams to translate business requirements into robust AI solutions.
• Research & Innovation: Investigate emerging AI techniques—such as deep learning, graph embeddings, and large language models—and assess their applicability to recommendation challenges.
• Model Deployment & Monitoring: Build production‑grade pipelines (using AWS, Docker, Spark, etc.) and establish monitoring frameworks to ensure model reliability, latency, and scalability.
• Data Exploration & Feature Engineering: Conduct deep dive analyses on user interaction data, content metadata, and contextual signals to uncover new personalization opportunities.
• Performance Benchmarking: Define and track KPI metrics (e.g., click‑through rate, dwell time, churn reduction) and continuously iterate on models to exceed targets.
• Best Practices & Documentation: Author clear documentation, coding standards, and testing protocols to foster knowledge sharing across the organization.
• Mentorship & Leadership: Guide junior engineers and data scientists, fostering a collaborative environment that encourages curiosity and rapid prototyping.

Essential Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field (or equivalent practical experience).
• 3+ years of hands‑on experience building AI/ML models for recommendation or personalization at scale.
• Proficiency in Python (or Scala) and deep familiarity with data‑science libraries such as TensorFlow, PyTorch, scikit‑learn, and Pandas.
• Demonstrated ability to design, implement, and maintain large‑scale data pipelines using technologies like AWS (S3, SageMaker), Docker, Apache Spark, and Databricks.
• Strong understanding of modern deep learning architectures (e.g., Transformers, CNNs, RNNs) and their mathematical foundations.
• Experience with natural language processing techniques, including contextual embeddings (e.g., BERT, RoBERTa) and tokenization strategies.
• Solid grasp of statistical concepts such as hypothesis testing, regression analysis, and causal inference.
• Excellent written and verbal communication skills, with the ability to convey complex technical ideas to both technical and non‑technical stakeholders.

Preferred Qualifications

• Master’s or Ph.D. in a quantitative discipline (Statistics, Machine Learning, Applied Mathematics, etc.).
• Prior experience developing content recommendation systems for streaming platforms or large‑scale media services.
• Hands‑on experience with graph‑based models (e.g., node2vec, GraphSAGE) for relationship‑driven recommendations.
• Track record of building end‑to‑end ML pipelines that include data ingestion, feature extraction, model training, A/B testing, and deployment.
• Familiarity with data visualization and analytics tools such as Looker, Tableau, or Superset.
• Experience with cloud‑native data warehouses (Snowflake, Redshift) and automated CI/CD workflows.
• Knowledge of metadata management, data lineage, and governance best practices.

Core Skills & Competencies

• Analytical Mindset: Ability to break down ambiguous problems, formulate hypotheses, and derive actionable insights from massive datasets.
• Product Thinking: Understanding of how recommendation algorithms impact user experience, revenue, and brand perception.
• Collaboration: Proven ability to work in multidisciplinary teams, balancing technical depth with business objectives.
• Agility: Comfort with rapid iteration, experimentation, and learning from failures in a fast‑paced environment.
• Ownership: Self‑driven attitude toward delivering high‑quality code, maintaining production stability, and driving projects to completion.
• Ethical AI Awareness: Commitment to fairness, transparency, and privacy considerations in recommendation systems.

Career Growth & Learning Opportunities

arenaflex invests heavily in the professional development of its employees. In this role, you will have access to:

• Mentorship from senior leaders in AI, product, and engineering.
• Sponsored attendance at industry conferences (e.g., RecSys, NeurIPS, KDD).
• Internal workshops on emerging technologies such as generative AI, reinforcement learning, and large‑scale distributed systems.
• Opportunities to lead cross‑functional initiatives that shape the strategic direction of arenaflex’s recommendation ecosystem.
• A clear promotion pathway from Senior Engineer to Staff Engineer, Principal Engineer, and eventually to AI Architecture leadership roles.

Work Environment & Culture at arenaflex

Our remote‑first culture empowers you to work from anywhere while staying deeply connected to a vibrant, inclusive community. arenaflex values:

• Innovation: A safe space to experiment, fail fast, and iterate.
• Diversity & Inclusion: A workforce that reflects the global audience we serve, fostering diverse perspectives and ideas.
• Work‑Life Balance: Flexible schedules, generous PTO, and a supportive environment that respects personal commitments.
• Collaboration: Regular virtual coffee chats, hackathons, and cross‑team syncs that keep the energy high and ideas flowing.
• Recognition: Quarterly awards, peer‑nominated accolades, and transparent performance feedback.

Compensation, Perks & Benefits

arenaflex offers a competitive compensation package that includes:

• Hourly rate of $25 (with performance‑based bonuses).
• Comprehensive health, dental, and vision coverage.
• Retirement savings plan with company match.
• Generous paid time off and holiday schedule.
• Professional development stipend for courses, certifications, and conferences.
• Home office allowance to support remote work setup.
• Access to arenaflex streaming services for personal enjoyment.
• Employee assistance programs and wellness resources.

How to Apply

If you are passionate about leveraging AI to craft unforgettable viewing experiences and thrive in a collaborative, data‑rich environment, we want to hear from you. Click the link below to submit your application and become a key contributor to arenaflex’s next wave of innovation.

Apply Now – Join arenaflex!

Closing Statement

At arenaflex, your expertise will directly shape the stories millions of viewers discover every day. Join us, push the boundaries of recommendation technology, and help define the future of entertainment. We look forward to welcoming a forward‑thinking, results‑driven engineer to our dynamic team.