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.
**This position is a full-time remote teleworker but may require occasional on-site meetings
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.
- 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
- 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
Pay Range:Pay Range $60,450.00 - $93,000.00 - $125,550.00