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 candidate should be able to quickly understand existing deployed machine learning models, big-data applications, text analytics, performance tuning, optimize, log analysis, issue resolution and continuous improvement to current operations.

　　The candidate should possess strong scripting skills in Python programming using Linux/Windows environments.

　　The candidate should be able to adopt to client needs, must be able to work independently and with other teams, guide the business team.

　　The candidate must possess strong written & oral communication, and collaboration skills.

　　Job Requirements:

　　BS/CS, MS/CS or equivalent.

　　2+ years of relevant 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 developing and managing pipelines using Databricks, manage user workspaces, notebooks, clusters and troubleshooting of Databricks using Ganglia.

　　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, Power BI 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.

　　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/Qualifications:

　　Masters Degree in Data Science.

　　Exposure to GenAI and applying LLMs to unstructured data.

　　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, QuickSight to communicate insights to a wide audience.

　　Programming experience using Java or C#.

　　Experience in using Linux CLI.

　　Pay Range:

　　Pay Range $65,000.00 - $117,500.00

　　The Leidos pay range for this job level is a general guideline onlyand 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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　　Original Posting Date:

　　01/23/2024

　　While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

　　REQNUMBER: R-00127213

　　All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. Leidos will consider qualified applicants with criminal histories for employment in accordance with relevant Laws. Leidos is an equal opportunity employer/disability/vet.