Senior Machine Learning Engineer

Master’s Degree or equivalent experience in Computer Science, Machine Learning, Artificial Intelligence, or a related field, with 2+ years working on Data Science, Machine Learning, and Agentic systems using Generative AI.
Strong experience in programming languages such as Python, R, Java, Scala.
Hands-on experience with machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn.
Proficiency in working with large-scale data analysis systems and cloud computing frameworks.
Experience in statistical modeling, predictive analytics, and deep learning techniques.
Strong problem-solving skills and the ability to translate complex algorithms into efficient code.
Excellent communication skills and ability to work collaboratively in a team environment.
Solid understanding of system architecture and distributed systems.
Experience with containerization and orchestration technologies like Docker and Kubernetes.
Familiarity with CI/CD pipelines and infrastructure as code tools.
Proven ability to build and maintain scalable microservices and integrate AI models into cloud-based infrastructures.

Architect and build robust, scalable AI systems that support AI agentic processes, enabling dynamic decision-making and personalized user experiences.
Leverage machine learning techniques such as decision trees, logistic regression, Bayesian analysis, and deep learning to build predictive and prescriptive models.
Apply deep learning and Generative AI technologies to enable advanced capabilities in Marketing Software, focusing on AI-driven Journey Optimization.
Develop end-to-end pipelines for training, deploying, and maintaining machine learning models in production environments.
Develop and program coordinated software algorithms for data analysis and decision-making in both product design and system improvement projects.
Ensure system reliability, performance, and scalability through testing, debugging, monitoring, and documentation.
Collaborate with cross-functional teams to integrate AI-driven insights into products and systems, ensuring seamless deployment and performance.
Stay updated with the latest advancements in artificial intelligence, machine learning, and Generative AI to continuously improve technological capabilities.

Experience in applying Generative AI to build AI agentic systems, with a focus on Building AI Agents.
Knowledge of distributed computing frameworks such as Spark and Hadoop for large-scale data processing.
Familiarity with deploying and maintaining machine learning models in production environments.
Understanding of AI-driven decision-making systems, reinforcement learning, and multi-agent systems.
Experience in building scalable microservices and integrating AI models into cloud-based infrastructures.