Designing and developing data-intensive software solutions and presenting a well-coordinated release cycle for model training and deployment by following proper guidelines and using statistical knowledge.
Documenting and monitoring important features, internal metrics, and changes shipped out in the release of new models for recommendation and fine-grained classification.
Designing, developing and productionizing Machine Learning models using technologies including scikit-learn, PyTorch, TensorFlow, NumPy, pandas, and Jupyter notebook.
Implementing algorithms for high-performance computing for machine learning applications using distributed systems and map reduce frameworks. Implementing multithreaded applications using Java for object-oriented programming, and Python for Machine Learning technologies such as neural networks using SQL for ETL and AWS technologies, including S3, KMS and Lambda.
Developing APIs and system architecture, pruning unnecessary complexities to ensure the system remains up to standards and user friendly.
Designing data interfaces for common Big Data storage and streaming pipelines such as Apache Arrow, ORC, Parquet or Spark, and MapReduce including working with Distributed Systems and data pipelines for Machine Learning systems.
Organizing regular touchpoints with the Product Manager and other stakeholders to develop new features to the Truera Platform and suggestions to meet customer needs requirements, identify problems scope, and recommend roadmap and prioritization.
Participating in early customer engagements making sure that Truera software integrates well with customers’ Machine Learning and data processing ecosystem by designing and developing event-driven asynchronous workflows to provide ML algorithm insights.
Setting up proof of concepts, and deploying micro-service architectures using Kubernetes or docker environments for customers and setting up RPC communication.
Reviewing, designing and writing application code to ensure quality control of final product.

Requirements/ Experience

Master’s(or foreign educ. equiv.) Degree in Computer Science, Computer Engineering or a related field and two (2) years’ experience in the job offered or related.
Developing and productionizing Machine Learning models
Using statistical knowledge
Use of python technologies for model development including scikit-learn, pandas and Jupyter notebook
Experience in distributed systems and Map reduce framework
Architecting and building ML pipelines, using SQL for ETL and AWS technologies including S3, KMS and Lambda
Designing and developing event-driven asynchronous workflows to provide customers with ML algorithm insights
Experience with micro-service architecture using Kubernetes for RPC communication
Using code versioning tools including Git
Must be authorized to work in the US w/o sponsorship