Big Data Machine Learning Developer

Description

Are you interested in making an immediate impact by improving and shaping the consumer fraud-protection industry? Would you like to play a critical role in protecting consumers from deceptive and unfair practices in the marketplace? Leidos, a Fortune 500 information technology, engineering and science solutions leader is seeking a Big Data Machine Learning Developer to join the team.

Leidos is looking for a strong Big Data Machine Learning Developer, who can design and develop complex machine learning models, Web API to consume the models, and deploy the solutions in distributed and/or cloud environment. The candidate should perform in a demanding, high-energy position requiring flexibility and innovative technical solutions to the challenges of processing, interpreting, and analyzing large volumes of data, including text.

We are seeking individuals with a unique blend of research and operational experience, to apply machine learning models and deep learning approaches to the problem of recognition in complex environments given sparse or limited training data.

• The individual should be able to quickly understand existing deployed machine learning models, big-data applications, performance tuning, optimize, log analysis, issue resolution and continuous improvement to current operations.
• The individual should possess strong scripting skills in Python programming using Linux/Windows environments.
• The individual should be able to adopt to client needs, must be able to work independently and with other teams, guide the business team.
• The individual must possess strong written & oral communication, and collaboration skills.

Job Requirements:

• BS/CS, MS/CS or equivalent
• 2+ years of experience in designing and building full stack solutions utilizing distributed computing using Python or Scala including distributed file systems or multi-node databases.
• Experience in one or more areas of machine learning / artificial intelligence such as classifications, NLP, Anomaly Detection, Sentiment Analysis, and Clustering
• Experience in using deep learning frameworks such as tensorflow, cntk, pytorch or keras, etc.
• Experience in solving NLP problems such as text categorization, text clustering/topic modeling, entity extraction, text summarization, etc.
• Experience in MLOps to operationalizing model building process and monitor machine learning models in production.
• Experience in effectively implementing clustering of unstructured data using unsupervised algorithms
• Experience in creating interactive data visualizations to create a compelling dashboard of the machine learning model results and performance in Tableau, PowerBI or other tools.
• Excellent understanding of common families of models, feature engineering, feature selection and other practical machine learning issues, such as overfitting
• Programming experience using Python (iPython notebooks), Matlab, R, or Scala
• Experience with distributed databases such as MongoDB, HBase, DynamoDB, Couch base, etc.
• Good skills in traditional databases such as MS-SQL with T-SQL, SSIS, SSAS or Oracle with PL/SQL, etc. Write optimized SQL queries, design database tables and structures, create views, functions, and stored procedures.
• Programming experience using Java or C#
• Excellent communication skills to communicate with wide technical and business users
• Demonstrate ability to build full stack systems architected for speed and distributed computing.
• Demonstrate ability to quickly learn new tools and paradigms to deploy cutting edge solutions
• Adept at simultaneously working on multiple projects, meeting deadlines, and managing expectations

Preferred Skills

• Experience or understanding in AWS SageMaker, Azure Machine Learning Studio, or similar ML/DS platform.
• Good exposure to cloud technologies such as AWS S3, Lambda functions, or Azure Data lake etc.,
• Knowledge of parallel computing approaches such as use of GPU parallelization is highly desirable
• Develop both deployment architecture and scripts for automated system deployment in AWS or on-premise systems.
• Create compelling data visualizations using Tableau, Power BI, Quick Sight to communicate insights to a wide audience

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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