Position: AI/ML Engineer

Location: Hyderabad (On-site)

Work Hours: Regular Experience: 2–4 years

Education:

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

Key Responsibilities:

• 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.

Required Skills:

• 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.