Machine Learning Engineer at Estrada International Staffing Solutions

Position Overview:

We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. As a Machine Learning Engineer, you will be responsible for developing, implementing, and deploying machine learning models and algorithms to solve complex business problems. You will collaborate with cross-functional teams to understand business requirements, design scalable solutions, and drive innovation through the application of cutting-edge machine learning techniques. The ideal candidate will have a strong background in machine learning, data analysis, and software engineering, with a passion for leveraging data-driven insights to drive business impact.

Key Responsibilities:

• Develop and implement machine learning algorithms and models to solve business problems across various domains, such as natural language processing, computer vision, recommendation systems, and predictive analytics.
• Design and build scalable, efficient, and reliable machine learning pipelines and systems for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Collaborate with data scientists, data engineers, and software developers to integrate machine learning solutions into production systems and applications.
• Conduct exploratory data analysis, feature engineering, and model evaluation to understand data characteristics and model performance.
• Stay up-to-date with the latest advancements in machine learning research and techniques, and proactively identify opportunities to apply them to improve our products and services.
• Work closely with stakeholders to understand business requirements, define success metrics, and deliver actionable insights through data-driven analysis and visualization.
• Communicate technical concepts and findings to non-technical stakeholders in a clear and concise manner.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. PhD is a plus.
• Solid understanding of machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models at scale.
• Proficiency in programming languages such as Python, R, or Java, and experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, or Spark MLlib.
• Strong analytical and problem-solving skills, with the ability to analyze large, complex datasets and derive actionable insights.
• Experience with data preprocessing, feature engineering, model selection, and hyperparameter tuning.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
• Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.