Artificial Intelligence/Machine Learning Engineer - Python

Job Description

Description Job Summary : The AI/ML Engineer will lead end-to-end design, development, and deployment of advanced, value-driven AI/ML solutions for digital marketing and analytics. Drive innovation, leverage cutting-edge techniques, and standardize multi-cloud model deployment through collaboration, delivering profound data insights. Required Qualifications Bachelor's degree (or higher preferred) in computer science, data science, ML, mathematics, statistics, economics, or related fields with emphasis on quantitative methods. 6-7 years' experience in software engineering with deep, hands-on expertise in the full lifecycle of ML model development, deployment, and operationalization. Demonstrated ability to write highly robust, efficient, and scalable Python, Java, Spark, and SQL code, adhering to industry best practices. Extensive experience with major ML frameworks (TensorFlow, PyTorch, and Scikit-learn) and advanced deep learning libraries, including optimization. Strong, in-depth understanding of diverse ML algorithms (e.g., advanced regression, classification, clustering, RNNs, CNNs, transformers, time series, reinforcement learning), sophisticated data structures, and enterprise software design. Significant experience deploying and managing AI/ML models on major cloud platforms (Azure, AWS, GCP). Proven experience with LLMs and generative AI (fine-tuning, prompt engineering, and deployment) is highly desirable. Exceptional problem-solving skills in a fast-paced, collaborative remote environment. Excellent communication and interpersonal skills, with the ability to effectively collaborate and influence diverse global teams remotely. Experience with classification, time series forecasting, customer lifetime value models, LLMs, and generative AI, preferably from the retail, eCommerce, or CPG industry. Responsibilities Lead cross-functional teams to deliver and scale complex AI/ML solutions (DL, NLP, optimization). Architect, design, develop, train, and evaluate high-performance, production-ready AI/ML models, ensuring scalability and robustness. Drive implementation, deployment, and maintenance of AI/ML solutions, optimizing inference and documenting processes. Oversee data exploration, advanced preprocessing, complex feature engineering, and robust data pipeline development. Establish strategies for continuous testing, validation, and monitoring of deployed AI/ML models to ensure accuracy and reliability. Partner with senior stakeholders to translate business requirements into scalable AI solutions that deliver measurable value. Act as a primary SME on AI/ML model development, MLOps, and deployment, influencing global data science platforms. Continuously research and champion the adoption of the latest AI/ML technologies, algorithms, and best practices to maximize business value. Foster innovative thinking and continuous improvement, seeking superior ways of working for teams and partners (ref:hirist.tech)