Senior Machine Learning Engineer (Recommendation Systems)

Job highlights

• 5-10 years in MLOps or ML infrastructure with expertise in AWS/GCP/Azure, Docker, Kubernetes, MLflow, and CI/CD pipelines
• Design, build, and operate scalable production ML systems including deployment, monitoring, retraining, and optimization

Senior Machine Learning Engineer (Recommendation Systems)

We are seeking a Senior Machine Learning Engineer to lead our content personalization efforts, shaping experiences that impact millions of users.

As a senior member of a growing team, you will tackle complex machine learning challenges and collaborate with data science, product, infrastructure, and backend engineering teams to deliver innovative, data-driven personalization solutions. Your work will directly impact content discovery, deepen user engagement, and drive long-term retention.

Responsibilities:

Lead development of recommendation systems: Design, build, and optimize advanced algorithms for SVOD, Live TV, and FAST personalization.

Drive ML innovation at scale: Conduct deep dives into models and system components, ensuring performance, scalability, and robustness across regions and product areas.

Own the ML pipeline: Build and maintain reliable pipelines for data extraction, feature engineering, model training, testing, and deployment.

Collaborate with Product, Data Science & Engineering: Translate product requirements into ML solutions, set clear expectations, and deliver measurable improvements in user engagement.

Advance deep learning in recommendations: Apply frameworks such as TensorFlow, PyTorch, or similar to develop state-of-the-art recommendation models.

Experimentation: Conduct rigorous A/B testing and ML experiments to understand model performance and iterate rapidly based on feedback.

ML Vision and Roadmap: Contribute to the strategic planning of the recommendations roadmap, aligning engineering efforts with business objectives and user needs.

Explore advanced architectures: Experience with frameworks like Two-Tower models and Deep Cross Networks (DCN) is a strong plus.

Qualifications:

8+ years of experience in backend engineering and/or data science, including 4+ years focused on machine learning. Experience with recommendation systems is a big plus.

Strong coding skills in Python, as well as proficiency in using ML frameworks like PyTorch or TensorFlow.

Excellent analytical and problem-solving skills, with the ability to translate complex technical challenges into business solutions.

Proven track record of leading projects and delivering impactful machine learning solutions.

Strong communication and documentation skills; capable of explaining complex, technical concepts to non-technical stakeholders and to diligently document your work to help the team as a whole learn and move quickly.

Experience with Amazon SageMaker or similar MLOps platforms