Senior Machine Learning Engineer

AEEC is seeking a Senior Machine Learning Engineer to join our team responsible for software development of machine learning solutions. Our team is growing and we are looking for a new team member to build a machine learning solution together with a highly multi-disciplinary team of engineers, scientists, and subject domain experts in building adaptive solutions.

In this role the candidate will partner with stakeholders, managers, engineers, and scientists to tackle machine learning problems using AI technology, perform experiments, and optimize the solutions. The candidate will be responsible for designing and maintaining machine/deep/reinforcement learning models and trying to optimize/customize them for new applications, developing production-ready software with scalable, fast and efficient algorithms, collecting data, performing data preprocessing, and defining performance indicators.

Education:

·    MSc or higher in computer science, statistics, mathematics, physical science, engineering, or a comparable related technical field

Job Duties:

• Develop highly scalable tools leveraging machine learning models to solve problems such as classification, detection, clustering, topic modeling, natural language processing and recommendation
• Research and implement deep learning, machine learning and statistical approaches to solve business problems
• Build models and present results to technical and non-technical business users
• Develop scalable data processing pipelines for analytical and predictive platform services
• Collaborate with other AI scientists and machine learning engineers to find effective solutions to technical challenges
• Provide recommendations, guidance and options to support AEEC’s AI/ML development roadmap
• Work closely with AI/ML engineers to build, test, deploy and troubleshoot machine learning/algorithm-based software

Required Skills:

• Strong computer science fundamentals, debugging skills and knowledge of algorithms
• Be able to develop significant code bases and integrate new libraries and frameworks into work
• Excellent foundation and demonstrable experience in recommendations and information retrieval algorithms
• Excellent coding abilities in Python and C/C++
• Be able to prototype products for ideating and testing
• Possess strong writing, data visualization and communication skills with the ability to communicate complex quantitative analysis in a clear, precise, and actionable manner to senior leaders and stakeholders
• Good understanding of foundational statistics concepts and algorithms: linear/logistic regression, random forest, boosting, Neural Networks, etc.
• Ability to access, manage, transfer, integrate and analyze complex datasets, especially using SQL or map-reduce techniques
• Familiarity with libraries such as SparkML, Tensorflow, scikit-learn, or others
• Broad understanding of the technologies and capabilities of Machine Learning and Deep Learnin
• Familiarity with style-transfer learning, unsupervised learning, training sets, and inference models
• Experience developing, training, and evaluating deep-learning models using public deep learning frameworks (e.g. PyTorch, TensorFlow, and Keras)
• Experience in deep networks (CNN, DBN, RNN, LSTM, DCN) or reinforcement learning (RL)
• Strong understanding of machine learning algorithms and principles
• Experience with open source vision packages such as OpenCV
• Experience with large data sets
• Exposure to GPU technology and CUDA programming

Preferred Skills:

• Ability to produce quantitative analysis benchmarking the performance of machine and deep learning algorithms/approaches against state-of-the-practice methods
• Experience with neural network design and implementation including, but not limited to, deep neural networks
• Excellent written, oral, and interpersonal communications skills

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