Principal .I​/Machine Learning Scientist

Principal Artificial Intelligence/Machine Learning Scientist

AEEC is seeking a Principal Artificial Intelligence/Machine Learning Scientist with neural networks deep learning experience who will lead a small team of AI scientists in solving AI problems and advancing AI techniques, science and research agendas of AI in one or more areas. The candidate will be responsible for leading and participating in the design, optimization, validation, and maintenance of large-scale machine learning (ML) models specific to AEEC's use case.

This involves data manipulation, data visualization, and programming. The candidate will also be expected to communicate the results of the analyses across different groups.

The candidate must have a consistent track record of successfully architecting and building highly available, low latency systems for high traffic applications, building machine learning and computer vision applications, a deep understanding of common families of models, feature engineering, feature selection and other practical machine learning and computer vision techniques. The candidate must also have a vision and experience to make end-to-end Machine Learning solutions, proven experience working in an environment building and shipping early-stage technologies, and foster a collaborative environment and bring fun to work.

Required Skills:

• Minimum of 10 years work experience with relevant AI, DL, and ML design and build experience
• Experience in the lifecycle of enterprise-class software development
• Expertise and experience in Machine Learning technologies (Tensor Flow, Keras, etc.)
• Team leadership skills
• Strong Python programming skills
• Experience conducting machine learning/statistical experiments and manipulating data sets
• Deep understanding and experience of machine learning, and deep learning theory, algorithms, approaches and practice, including probabilistic and statistical learning, graphical models, machine perception, machine comprehension, neural networks, deep learning, computer vision and other machine learning areas
• Hands on and strong programming experience in one or more of the leading AI, machine learning and deep learning open source libraries
• Strong proficiency with computer vision, natural language processing and deep learning
• Strong understanding of machine learning algorithms and principles
• Expertise and experience in using or developing AI and machine learning algorithms, such as supervised and unsupervised learning, deep learning, reinforcement learning and others, to solve applied problems in various disciplines
• Experience developing, training, and evaluating deep-learning models using deep learning frameworks (e.g. PyTorch, Tensor Flow, and Keras)
• Experience with open source vision packages such as OpenCV
• Familiarity with CUDA and GPU computing
• Strong proficiency with Python, C/C++

Education:

• Ph.D. in a quantitative science:
  Computer Science, Math, Electrical Engineering, Statistics, or relevant program with major in AI, Machine Learning, or Computational Linguistics

Preferred

Skills:

• Excellent technical communication skills
• Recognized expertise in artificial intelligence and machine learning applications as evidenced by relevant publications or awards
• Track record of research excellence and high quality publications

Job Duties:

• Provide technical leadership in the execution of AEEC's AI projects
• Lead a small team of AI scientists in solving AI problems and advancing AI techniques, science and research agendas of AI in one or more areas
• Lead and drive architecting and coding of AI algorithms, Machine Learning architectures and pipelines, for building ML/DL capabilities delivered in an AI platform including training, evaluation and management of AI models
• Direct the technical leadership of one or more AI projects through Pilot phases
• Maintain expert knowledge in state-of-the-art AI, ML and Deep Learning approaches
• Actively engage with the AI community and the broader academic community
• Maintain a good working knowledge of the offerings of major AI vendors and technologies
• Build end-to-end machine learning systems – consistent model training, evaluation, deployment and delivery for batch, streaming or…