Machine Learning Engineer - Python/Spark

Job Description
 Minimum 5 years" experience in Object Oriented Design and Programming and Python development.
 Experience implementing machine learning frameworks and libraries
 Development experience with a JavaScript framework, experience building machine learning pipelines in Microsoft Azure Machine Learning service
 Experience developing cloud first solutions using Microsoft Azure Services
 Working knowledge of mathematics (primarily linear algebra, probability, statistics), and algorithms.
 Must have a disciplined, methodical, minimalist approach to designing and constructing layered software components that can be embedded within larger frameworks or applications.
 Proficient at orchestrating large-scale ML/DL jobs, leveraging big data tooling and modern container orchestration infrastructure, to tackle distributed training and massive parallel model executions on cloud infrastructure.
 Experience designing custom APIs for machine learning models for training and inference processes and designing, implementing, and delivering frameworks for MLOps.
 Experience implementing and incorporating ML models on unstructured data using cognitive services and/or computer vision as part of AI solutions and workflows.
 History of working with large scale model optimization and hyperparameter tuning, applied to ML/DL models.
 Hands-on experience in deploying machine learning pipelines with Azure Machine Learning SDK.

Knowledge of enterprise SaaS complexities including security/access control, scalability, high availability, concurrency, online diagnoses, deployment, upgrade/migration, internationalization, and production support.
 Knowledge of data engineering and transformation tools and patterns such as DataBricks, Spark, Azure Data Factory.
 Mature software engineering skills, such as source control versioning, requirement spec, architecture and design review, testing methodologies, CI/CD, etc.
 Ability to engage business and technical experts at all organizational levels and assess opportunities to apply machine learning and analytics to improve their workflows and deliver information and insight to support business decisions.
 Ability to communicate in a clear, concise, and understandable manner both orally and in writing.

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