Responsibilities:

Lead the design, development, and implementation of AI models and algorithms to solve complex business problems.
Oversee and mentor a team of AI engineers and data scientists, providing technical guidance and fostering a collaborative environment.
Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Conduct research and stay up to date with the latest advancements in AI and machine learning, integrating new technologies and methodologies into the team's workflows.
Optimize and fine-tune AI models for performance, scalability, and accuracy.
Develop and maintain AI pipelines and workflows, ensuring best practices in data management and model deployment.
Perform data preprocessing, feature engineering, and model evaluation.
Deploy AI models into production environments and monitor their performance.
Communicate AI strategies and progress to stakeholders, including senior management and non-technical audiences.
Ensure AI solutions adhere to ethical guidelines and responsible AI practices.
Develop and execute a strategic vision for the AI team, aligning with the company's goals and objectives.
Manage project timelines, deliverables, and resources to ensure successful project completion.
Foster a culture of continuous learning and innovation within the AI team.

Required Skill Sets:

Educational Background: Bachelor's or master's degree in computer science, Artificial Intelligence, Machine Learning, or a related field. A PhD is a plus.
Programming Languages: Proficiency in Python, R, or Java. Experience with libraries and frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn, etc.
Machine Learning: Extensive knowledge of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
Data Science: Experience with data analysis, data visualization, and statistical modeling. Proficiency in using tools like Pandas, NumPy, Matplotlib, and Seaborn.
Big Data Technologies: Familiarity with big data processing frameworks like Hadoop, Spark, or Apache Flink.
Cloud Platforms: Experience with cloud services such as AWS, Google Cloud, or Azure for deploying AI solutions.
Natural Language Processing (NLP): Knowledge of NLP techniques and tools such as NLTK, SpaCy, or GPT-3.
Computer Vision: Experience with computer vision techniques and libraries such as OpenCV, YOLO, or Fast R-CNN.
Leadership: Proven experience in leading and managing a team of engineers or data scientists. Strong leadership and mentorship skills.
Problem-Solving: Strong analytical and problem-solving skills with the ability to think critically and creatively.
Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Team Collaboration: Ability to work effectively in a collaborative team environment and contribute to team success.
Strategic Vision: Ability todevelop and execute a strategic vision for the AI team, aligning with the company's goals and objectives.
Project Management: Experience in managing project timelines, deliverables, and resources to ensure successful project completion.

Preferred Qualifications:

Experience with AI ethics and responsible AI practices.
Knowledge of DevOps practices and tools for continuous integration and deployment (CI/CD).
Familiarity with Agile methodologies and project management tools.
Previous experience in a leadership role within an AI or data science team.

AI Developer, Machine Learning (A128)

AI Developer

AI Lead Developer