Ai Ml Engineer

Hi,

PFB Job description, kindly connect and let me know if interested or Share your CV on sairam.m.naik@pwc.com or if you have any references it will be helpful.

Responsibilities:

• Collaborate with business stakeholders to understand problem statements and translate them into analytical solutions.
• Design, develop, and deploy predictive models including classification, regression, clustering, and time-series forecasting models.
• Perform exploratory data analysis (EDA), data cleaning, preprocessing, and feature engineering on structured and unstructured datasets.
• Apply statistical techniques including hypothesis testing and experimental design to validate insights and model performance.
• Work closely with data engineers to build and maintain scalable data pipelines and ensure efficient data processing.
• Deploy machine learning models into production environments using APIs and containerization technologies.
• Implement MLOps best practices including model versioning, monitoring, CI/CD integration, and model registries.
• Utilize cloud platforms such as Azure, AWS, or GCP for model training, deployment, and scaling.
• Develop interactive dashboards and visualizations using tools such as Power BI, Tableau, Matplotlib
• Communicate findings and insights to technical and non-technical stakeholders through reports, presentations, and data storytelling.
• Stay updated with the latest advancements in machine learning, AI, and data science methodologies to drive innovation.

Requirements:

• Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 4–6+ years of relevant experience in data science, machine learning, or applied statistics.
• Strong programming proficiency in Python (pandas, NumPy, scikit-learn, statsmodels) and/or R.
• Experience building and validating predictive models (classification, regression, clustering, time-series).
• Strong understanding of statistics, hypothesis testing, and experimental design.
• Proficiency in SQL and experience working with structured and unstructured datasets.
• Hands-on experience with machine learning frameworks such as scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Experience deploying ML models into production using FastAPI or similar frameworks.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience working with cloud platforms such as Azure ML, AWS SageMaker, or GCP Vertex AI.
• Experience with Spark (PySpark), Databricks, or large-scale data processing frameworks.
• Knowledge of MLOps tools such as MLflow, model registries, and CI/CD pipelines.
• Experience working with SQL/NoSQL databases, Data Lakes, and Blob Storage.
• Strong analytical, problem-solving, and communication skills.
• Ability to work in a fast-paced and dynamic environment.

Nice to Have Skills:

• Experience working on AI/LLM-enabled analytics solutions.
• Exposure Generative AI or advanced AI frameworks.
• Experience in building data products or end-to-end ML platforms(pandas,Keras, Tensorflow).
• Relevant certifications in Data Science, Cloud, or Machine Learning technologies.

Preferred Qualifications:

• BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Master’s Degree / MBA from a reputed institute