Senior Machine Learning Engineer (EMEA)

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Our machine learning team is seeking an experienced senior machine learning engineer. The team is in need of someone who is a skilled software engineer and proficient in ML libraries, system design and pipelines. As a machine learning engineer, you will be building state-of-the-art models for our products, using test driven development, and working with the software engineering team to deploy and maintain the models in production.

Job Duties/Responsibilities

• Design, train and deliver machine learning solutions to a wide range of datasets: from small datasets to big data, time series to 3D matrices, both unlabeled and labeled 
• Collaborate with the development team and ML engineers to implement, test and validate new algorithms and integrate the algorithms with the existing frontend and backend systems. 
• Build state-of-the-art models for various modeling tasks (e.g., time series forecasting, spatiotemporal and traffic/logistic) 
• Optimize and automate model training and testing, experimentation tracking, development, and production. 
• Skilled in breaking down problems, documenting problem statements and estimating efforts
• Mentor junior engineers, perform code reviews and document design decisions
• Create web services/APIs for serving ML/AI model results. 

Minimum Qualifications

• PhD or MS in Computer Science, Electrical Engineering or similar field 
• 8+ years of experience with one modern language such as Java, C++, Python including object-oriented design. 
• 5+ years of experience with machine learning tools and deep learning algorithms and techniques, including but not limited to:

• PyTorch, TensorFlow, Keras
• CNN, LSTM, RNN 
• Scikit-learn, pandas, numpy 
• Optimization techniques and fine-tuning models

• 3+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems. 
• Experience with MLOps and other production level implementation frameworks and pipelines
• Experience with messaging systems, Docker, Kubernetes, Spark, EMR, and cloud platforms (AWS or Azure) 
• Able to work independently on problems and in highly collaborative team environments. 

Preferred Qualifications

• Team management and mentoring junior members
• Graph-based Machine Learning 
• Research experience with high impact publications
• Application of ML in industrial projects