Job Title: Data Scientist / Machine Learning Engineer 

Location: [Remote/On-site] 

Experience Level: 5+ years 

Department: AI/ML Research & Development 

About the Role 

We are seeking a Data Scientist / ML Engineer to contribute to the development of advanced AI-driven applications. The role involves designing, building, and optimizing machine learning models for personalized recommendations, content analysis, and user experience enhancement. You will work in collaboration with backend, DevOps, and data science teams to develop scalable ML solutions integrated into a cloud-based infrastructure. 

Key Responsibilities 

• Develop machine learning algorithms for recommendation systems, content understanding, and personalization. 
• Work on user-context-aware ML models to improve engagement and experience. 
• Research, prototype, and optimize scalable ML solutions, ensuring high performance. 
• Collaborate with backend engineers to integrate models into production environments. 
• Deploy and monitor ML pipelines in collaboration with DevOps teams. 
• Experiment with feature engineering, metadata extraction, and model tuning to enhance accuracy. 
• Analyze existing ML approaches in similar products and assess their strengths and limitations. 

Required Skills & Experience 

• Proficiency in ML and Deep Learning: Supervised & unsupervised learning, personalization techniques, and content-based modeling. 
• Programming: Python (TensorFlow, PyTorch, Scikit-learn), SQL, and cloud-based ML deployment (AWS/GCP/Azure). 
• Recommendation Systems: Experience with collaborative filtering, content-based filtering, and ranking models. 
• Scalable ML Deployment: Understanding of cloud infrastructure, containerized ML models (Docker, Kubernetes), and API-based inference. 
• Collaboration & Communication: Ability to work with cross-functional teams in a fast-paced environment. 

Preferred Qualifications 

• Hands-on experience with ML Ops tools (MLflow, Kubeflow). 
• Familiarity with vector search (FAISS, Milvus) for retrieval-based ML models. 
• Experience with audio, video, or text analysis is a plus. 
• Contributions to open-source ML projects or AI/ML research papers.