Machine Learning Engineer

You will be responsible for exploring and visualizing data to gain insights and identify differences in data distribution that may impact model performance in real-world deployment. You will verify data quality through data cleaning and work efficiently to enhance decision-making for stakeholders using Machine Learning. Your role will involve designing and developing Machine Learning systems, conducting statistical analysis, and fine-tuning models based on test results. Additionally, you will be required to train and retrain ML systems as needed, deploy models in production, and manage cloud infrastructure costs. Developing Machine Learning applications tailored to client and data scientist needs will be part of your responsibilities, as well as evaluating the problem-solving capabilities of ML algorithms and ranking them based on their success in meeting objectives. In terms of technical knowledge, you should have experience in addressing real-time problems using ML and deep learning models deployed in real-time, with a portfolio of impactful projects. Proficiency in Python and familiarity with Jupyter Framework, Google Colab, and cloud-hosted notebooks like AWS SageMaker and DataBricks is essential. You should also be well-versed in libraries such as Scikit-learn, TensorFlow, OpenCV2, PySpark, Pandas, NumPy, and related tools, and have expertise in visualizing and manipulating complex datasets using libraries like Seaborn, Plotly, and Matplotlib. Strong knowledge of linear algebra, statistics, and probability for Machine Learning is required, along with proficiency in ML algorithms (e.g., Gradient Boosting, stacked ML, classification algorithms, and deep learning) and experience in hyperparameter tuning and model performance comparison. Moreover, familiarity with big data technologies like the Hadoop stack and Spark, basic cloud usage (e.g., VMs like EC2), and bonus points for Kubernetes and Task Queues will be advantageous. Effective written and verbal communication skills, along with experience working in an Agile environment, are essential for this role. Key Skills: Python, Big Data, Apache Spark, Machine Learning (ML), Deep Learning.,