Senior Machine Learning Engineer

Job Description

We are seeking a talented AI/ML Engineer to join our team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will be responsible for designing, developing, and deploying machine learning models and AI algorithms that drive our products and services. This role requires a deep understanding of data processing, model training, and deployment, as well as the ability to collaborate with cross-functional teams to integrate AI solutions into our technology stack. Responsibilities; Model Development: Design, develop, and implement machine learning models and AI algorithms to solve complex problems and improve business outcomes. Experiment with different machine learning techniques, including supervised, unsupervised, and reinforcement learning. Optimize models for performance, scalability, and accuracy. Data Management: Collect, clean, and preprocess large datasets for training and evaluating machine learning models. Work with data engineers to ensure data pipelines are robust, efficient, and scalable. Conduct exploratory data analysis to understand data patterns and relationships. Deployment and Integration: Deploy machine learning models in production environments, ensuring robustness and reliability. Collaborate with software engineers to integrate AI/ML solutions into existing systems and applications. Monitor and maintain deployed models, performing updates and retraining as necessary. Research and Innovation: Stay up-to-date with the latest advancements in AI and machine learning technologies. Experiment with new algorithms, frameworks, and tools to push the boundaries of what our AI solutions can achieve. Contribute to research publications, patents, and internal knowledge sharing. Collaboration: Work closely with product managers, data scientists, software engineers, and other stakeholders to define project requirements and deliver high-quality AI solutions. Participate in code reviews, pair programming, and knowledge-sharing sessions. Required Qualifications; Bachelor s or Master s degree in Computer Science, Engineering, Mathematics, or a related field. Proven experience (5+ years) in developing and deploying machine learning models in a production environment. Strong programming skills in languages such as Python, R, Java, or C++. Experience with machine learning frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn. Proficiency in working with large datasets, SQL and NoSQL databases, and data processing tools (e.g., Pandas, NumPy). Solid understanding of algorithms, data structures, and statistical methods. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying AI/ML models. Strong problem-solving skills, with the ability to work independently and as part of a team. Technical Skills; Experience with deep learning architectures such as CNNs, RNNs, or Transformers. Knowledge of natural language processing (NLP), computer vision, or reinforcement learning. Familiarity with DevOps practices, including CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes). Experience with big data technologies such as Hadoop, Spark, or Hive. Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.