Software Design Engineer – .NET, Azure, AI/ML (H)

Software Design Engineer – .NET, Azure, AI/ML 16579 – 132970 (H)

A leading tech company is seeking Software Design Engineer – NET, Python – Citizen/GC. The ideal candidate has experience working with Government Procurement, Anti-Money Laundering, and Investigations. The company offers a great work environment!

Software Design Engineer – .NET, Azure, AI/ML Pay and Benefits:

• Hourly pay: $40/hr
• Worksite: Leading technology and data solutions company (Remote, must be able to work EST hours)
• W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program
• 40 hours/week, 11 Month Assignment

Software Design Engineer – .NET, Azure, AI/ML Responsibilities:

• Data Preparation and Understanding:

• Understand problems facing projects to leverage the knowledge of data science to be able to uncover important factors that can influence outcomes on specific products.
• Acquire data necessary for the successful completion of the project plan. Proactively detect changes and communicates to senior leads.
• Develop useable data sets for modeling purposes. Contribute to ethics and privacy policies related to collecting and preparing data by providing updates and suggestions around internal best practices. Contribute to data integrity/cleanliness conversations with customers.
• Modeling and Statistical Analysis:

• Understand modeling techniques (e.g., dimensionality reduction, cross-validation, regularization, encoding, assembling, activation functions) and select the correct approach to prepare data, train and optimize the model, and evaluate the output for statistical and business significance. Understand the risks of data leakage, the bias/variance tradeoff, methodological limitations, etc.
• Leverage knowledge of machine learning solutions (e.g., classification, regression, clustering, forecasting, NLP, image recognition, etc.) and individual algorithms (e.g., linear and logistic regression, k-means, gradient boosting, autoregressive integrated moving average [ARIMA], recurrent neutral networks [RNN], long short-term memory [LSTM] networks) to identify the best approach to complete objectives.
• Write all necessary scripts in the appropriate language: T-SQL, U-SQL, KQL, Python, R, etc. Construct hypotheses, design controlled experiments, analyze results using statistical tests, and communicate findings to business stakeholders.
• Effectively communicate with diverse audiences on data quality issues and initiatives. Understand operational considerations of model deployment, such as performance, scalability, monitoring, maintenance, integration into the engineering production system, and stability.
• Develop operational models that run at scale. Develop a strong understanding of the toolset in artificial intelligence (AI) and machine learning (ML) (e.g., Azure Machine Learning, Azure Cognitive Services, Azure Databricks, Synapse). Break down complex statistics and machine learning topics into manageable topics to explain to customers.
• Help the Solution Architect and provide guidance on model operationalization that is built into the project approach using existing technologies, products, and solutions, as well as established patterns and practices.
• Evaluation:

• Understand the relationship between selected models and business objectives. Ensure clear linkage between selected models and desired business objectives. Assess the degree to which models meet business objectives. Define and design feedback and evaluation methods. Present results and findings to senior customer stakeholders.
• Industry and Research Knowledge/Opportunity Identification:
• Leverage capabilities within existing systems. Share knowledge of the industry through conferences, white papers, blog posts, etc. Research and maintain deep knowledge of industry trends, and technologies, and contribute to the body of thought leadership and intellectual property (IP) best practices.
• Coding and Debugging:

• Write efficient, readable, extensible code from scratch that spans multiple features/solutions. Develop technical expertise in proper modeling, coding, and/or debugging techniques such as locating, isolating, and resolving errors and/or defects.
• Understand the causes of common defects and use best practices in preventing them from occurring.
• Collaborate with other teams and leverage best practices from those teams into the work of their own team.
• Build professional-grade documents for knowledge transfer and deployment of predictive analytic models.
• Leverage technical proficiency in big-data software engineering concepts, such as Hadoop Ecosystem, Apache Spark, continuous integration and continuous delivery (CI/CD), AzDo, Docker, Delta Lake, MLflow, AML, and representational state transfer (REST) application programming interface (API) consumption/development.

Software Design Engineer – .NET, Azure, AI/ML Qualifications:

• 3-5 years of software design experience.
• Experience working with Government Procurement, Anti-Money Laundering, and Investigations.
• Coding experience with AI & ML.
• Working knowledge of Agile Development Processes/Azure Dev Ops.
• Working Knowledge of Azure Cloud Services.
• C, C++, C#, Java, JavaScript, or Python.