AI/ML Engineer (2-5 Years Experience | Immediate Joiner | Remote)

About the job: About the Role Our client is seeking an AI/ML Engineer to build intelligent decision systems that help businesses make better data-driven decisions. The ideal candidate will have hands-on experience building production ML systems and the ability to translate ambiguous business problems into practical machine learning solutions that create measurable business impact. This role focuses on real-world problem-solving, model evaluation, recommendation systems, ranking systems, retrieval, forecasting, and decision-support workflows rather than simply training models. Key Responsibilities Design, develop, and deploy production-grade machine learning systemsBuild recommendation systems, ranking models, and retrieval-based solutionsDevelop prediction, forecasting, clustering, anomaly detection, and optimization modelsWork with embeddings, similarity search, and representation learning techniquesBuild data processing pipelines and production-ready ML workflowsPerform feature engineering, exploratory data analysis (EDA), and behavioral modelingDefine evaluation frameworks and measure both model performance and business impactTranslate business challenges into machine learning problems and identify meaningful signals in complex datasetsAnalyze model failures, optimize performance, and improve reliabilityCollaborate with product and engineering teams to deliver scalable, data-driven solutionsBalance model quality, operational constraints, and business objectives when designing solutions Required Skills 25 years of hands-on experience building production ML systemsExperience shipping at least one machine learning-powered feature or workflow into productionStrong understanding of supervised learning, feature engineering, and model evaluationExperience with recommendation systems, ranking systems, embeddings, and representation learningKnowledge of experimentation methodologies, model debugging, and performance analysisStrong understanding of offline and online model evaluation techniquesSolid grasp of bias-variance tradeoffs, precision-recall tradeoffs, calibration, overfitting, and distribution shift conceptsStrong programming skills in Python, Pandas, NumPy, and SQLExperience building data processing pipelines and working with production codebasesExperience with APIs and data integrationsAbility to work with real-world datasets and measure business impactStrong analytical thinking, problem-solving, and communication skills Nice-to-Have Skills Experience with cloud platforms, distributed systems, orchestration frameworks, or MLOps toolsExperience building recommendation, ranking, search, or retrieval systemsKnowledge of forecasting, optimization, and experimentation frameworksExperience deploying ML systems into production environmentsBackground in commerce, marketplace, SaaS, or consumer product domainsExperience building data products with measurable business outcomesFamiliarity with modern AI systems and hybrid ML/AI architectures About YMinds.AI YMinds.AI is a talent solutions and consulting firm that connects top-tier technology professionals with forward-thinking organizations. We specialize in delivering curated talent aligned with evolving business and technology needs. Keywords Applied Machine Learning Engineer, Machine Learning, Recommendation Systems, Ranking Systems, Retrieval Systems, Forecasting, Anomaly Detection, Feature Engineering, Python, Pandas, NumPy, SQL, Embeddings, Similarity Search, Data Science, Production ML, Model Evaluation Hashtags #MachineLearning #AppliedML #DataScience #PythonDeveloper #RecommendationSystems #ArtificialIntelligence #Forecasting #MLEngineer #HiringNow #TechJobs #YMindsAI Who can apply: Only those candidates can apply who: have minimum 2 years of experience Salary: Competitive salary Experience: 2 year(s) Deadline: 2035-01-01 00:00:00 About the job: About the Role Our client is seeking an AI/ML Engineer to build intelligent decision systems that help businesses make better data-driven decisions. The ideal candidate will have hands-on experience building production ML systems and the ability to translate ambiguous business problems into practical machine learning solutions that create measurable business impact. This role focuses on real-world problem-solving, model evaluation, recommendation systems, ranking systems, retrieval, forecasting, and decision-support workflows rather than simply training models. Key Responsibilities Design, develop, and deploy production-grade machine learning systemsBuild recommendation systems, ranking models, and retrieval-based solutionsDevelop prediction, forecasting, clustering, anomaly detection, and optimization modelsWork with embeddings, similarity search, and representation learning techniquesBuild data processing pipelines and production-ready ML workflowsPerform feature engineering, exploratory data analysis (EDA), and behavioral modelingDefine evaluation frameworks and measu