Machine Learning Engineer - Recommendation Systems

Company: Apna

Location: patna

Employment type: Full time

Salary: INR 50000-70000 (Per Month)

Category: Other

We are hiring a Machine Learning Engineer to develop and deploy advanced ML models for content recommendation, friend suggestions, ad targeting, and search ranking. You will work with massive datasets to train deep learning models and optimize them for real-time predictions at billion-user scale. This is a high-impact role where your work directly influences what billions of users see on their feeds.Key Responsibilities:• Design, build, and productionize ML models for feed ranking, content recommendation, and user matching• Work with massive datasets (petabyte-scale) to train and evaluate deep learning models• Optimize model latency and accuracy for real-time predictions (sub-100ms response times)• Build feature engineering pipelines and model serving infrastructure• Collaborate with data scientists, backend engineers, and product managers to define ML requirements• Implement A/B testing frameworks for model evaluation and business impact measurement• Monitor model performance, detect data drift, and implement retraining strategies• Research and apply state-of-the-art techniques in NLP, computer vision, and graph neural networks• Write production-quality ML code with proper testing, logging, and documentationQualifications & Requirements:• Master's or PhD in Computer Science, Machine Learning, Statistics, or related quantitative field• 4+ years of experience building and deploying ML models in production environments• Expert-level proficiency in Python and ML frameworks (TensorFlow, PyTorch, JAX, Scikit-learn)• Strong understanding of deep learning architectures: Transformers, CNNs, RNNs, GNNs• Experience with large-scale data processing (Spark, Hadoop, BigQuery, Snowflake)• Proficiency in feature stores, model versioning (MLflow), and model serving (Triton, TorchServe)• Solid foundation in statistics, linear algebra, calculus, and optimization algorithms• Experience with real-time inference systems and model compression/quantization techniques• Strong software engineering skills with experience in distributed systems• Excellent problem-solving abilities and research mindsetPreferred Qualifications:• Publications in top-tier ML conferences (NeurIPS, ICML, ICLR, KDD)• Experience with reinforcement learning for recommendation systems• Knowledge of causal inference and uplift modeling• Familiarity with MLOps practices and Kubeflow/Vertex AI pipelines