AI / ML Engineer

Position: AI/ML Engineer Location: Hyderabad (On-site) Work Hours: Regular Experience: 2–4 years

: • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field.

: • Design, build, train, evaluate, and deploy machine learning models for predictive, classification, ranking, anomaly detection, forecasting, and optimization use cases. • Develop AI/ML solutions that enhance agentic AI systems by supplying predictive intelligence, structured scoring, recommendations, and decision-support signals. • Perform data preparation, feature engineering, dataset analysis, and model experimentation across structured and unstructured data sources. • Apply supervised and unsupervised learning techniques, hyperparameter tuning, cross-validation, and statistically sound evaluation methods. • Build NLP- and LLM-enabled solutions where applicable, including text classification, information extraction, semantic similarity, summarization support, and hybrid AI systems. • Integrate machine learning models into backend services, APIs, dashboards, workflow engines, and enterprise applications for real-world production use. • Implement model deployment, versioning, monitoring, retraining, and lifecycle management practices to ensure accuracy, reliability, and long-term value. • Collaborate closely with data engineers to improve data pipelines and feature availability, and with backend and AI engineers to embed models into larger intelligent systems. • Establish evaluation metrics, performance benchmarks, drift detection, feedback loops, and monitoring dashboards. • Translate ambiguous business problems into well-defined, modelable use cases with measurable outcomes and clear deployment strategies. • Support experimentation, pilot implementations, and continuous improvement of AI/ML solutions across automation, analytics, operations, and decision-making workflows.

: • 2–4 years of hands-on experience in machine learning model development, validation, deployment, and production support. • Strong proficiency in Python with practical experience in ML-focused development. • Solid understanding of machine learning fundamentals, including supervised and unsupervised learning, feature engineering, and model evaluation. • Hands-on experience with core ML and data libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch. • Experience with NLP, text analytics, LLM-assisted workflows, or deep learning use cases relevant to enterprise AI. • Experience integrating ML models with backend systems, APIs, and enterprise applications. • Familiarity with MLOps concepts, including model deployment, monitoring, retraining, and CI/CD for ML. • Experience working with Azure ML or Azure-based AI/ML services. • Strong analytical, problem-solving, and debugging skills. • Good communication skills with the ability to clearly explain and document technical concepts.