AI/ML Engineer

The ideal candidate should have strong expertise in Python, AI/ML algorithms, SQL, PySpark, and Generative AI technologies. You will work closely with data engineers, product teams, and business stakeholders to build scalable and impactful AI-driven solutions.Key ResponsibilitiesDesign, develop, and deploy machine learning models and AI solutions.Build and optimize data pipelines using PySpark for large-scale data processing.Develop and implement Generative AI solutions using modern frameworks and APIs.Perform data preprocessing, feature engineering, and model evaluation.Write efficient SQL queries for data extraction, transformation, and analysis.Deploy ML models into production environments and monitor model performance.Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.Optimize model accuracy, scalability, and performance.Stay updated with the latest advancements in AI/ML and Generative AI technologies.Required Skills & Qualifications4+ years of experience in AI/ML development.Strong proficiency in Python.Hands-on experience with machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch.Experience with Generative AI (LLMs, prompt engineering, embeddings, RAG frameworks, etc.).Strong knowledge of SQL for data querying and manipulation.Experience working with PySpark and big data processing frameworks.Solid understanding of statistics, data structures, and algorithms.Experience with model deployment and MLOps practices is a plus.Strong problem-solving and analytical skills.Preferred QualificationsExperience working with cloud platforms (AWS/GCP/Azure).Exposure to REST APIs and microservices architecture.Experience with version control tools like Git.Knowledge of CI/CD pipelines for ML deployment.Skills: sql,ai/ml,pyspark,genai,data scientist,aws,docker,ml,machine learning,python