Senior AL/ML Engineer - REMOTE

D.P. Consulting is looking for a highly skilled Senior AI/ML Engineer with over 10 years of experience in artificial intelligence and machine learning. The ideal candidate will have a deep understanding of AI/ML concepts, algorithms, and technologies, with a proven ability to design, develop, and deploy advanced machine learning models and AI systems. This role requires a visionary who can lead AI/ML initiatives, mentor junior engineers, and contribute to the company’s growth through innovative solutions.

Responsibilities:

• Lead the design, development, and deployment of AI/ML models and systems to solve complex business problems.
• Collaborate with cross-functional teams, including data scientists, data engineers, and software developers, to integrate AI/ML solutions into production environments.
• Develop and optimize machine learning algorithms, including supervised, unsupervised, and reinforcement learning models.
• Implement and fine-tune deep learning models, such as CNNs, RNNs, and transformers, for various applications like computer vision, NLP, and predictive analytics.
• Work with large datasets to conduct exploratory data analysis, feature engineering, and model training.
• Stay up-to-date with the latest advancements in AI/ML technologies and incorporate them into ongoing projects.
• Mentor and guide junior AI/ML engineers, providing technical leadership and promoting best practices.
• Evaluate and select appropriate AI/ML tools, libraries, and frameworks to meet project requirements.
• Monitor and maintain AI/ML models in production, ensuring performance, accuracy, and scalability.
• Communicate complex technical concepts to non-technical stakeholders, providing insights and recommendations based on data-driven results.

• Machine Learning Algorithms: Extensive knowledge of supervised, unsupervised, and reinforcement learning techniques.
• Deep Learning: Proficiency in neural networks, particularly CNNs, RNNs, and transformers.
• Programming: Strong skills in Python, R, or other relevant programming languages.
• AI/ML Frameworks: Expertise in TensorFlow, PyTorch, Scikit-learn, Keras, or similar libraries.
• Cloud Platforms: Experience with AWS SageMaker, Azure ML, Google AI Platform, or equivalent.
• Big Data: Familiarity with big data processing tools like Hadoop, Spark, or similar.
• Data Handling: Proficiency in data preprocessing, feature engineering, and model evaluation techniques.
• MLOps: Experience with MLOps practices, including CI/CD pipelines, version control, and model monitoring.

Communication: Strong verbal and written communication skills, with the ability to convey complex AI/ML concepts to diverse audiences.