Leidos is looking for a 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.
-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, in order 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, performance tuning, optimize, log analysis, issue resolution and continuous improvement to current operations.
-Strong scripting skills in Java and Python programming in Linux and Windows environments. -Adopt to client needs, must be able to work independently and also with other teams, guide the business team, and must possess strong written & oral communication and collaboration skills.
Required Education & Experience:
-Requires a Bachelor's degree in Computer Science or related and 2+ years of experience in designing and building full stack solutions utilizing distributed computing using Python, Scala or Java including distributed file systems or multi-node databases.
-Ability to obtain and maintain a Public Trust clearance.
-Experience in one or more areas of machine learning / artificial intelligence such as classifications, pattern recognition, NLP, Anomaly Detection, Recommender Systems, Sentiment Analysis, Clustering, Decision Trees, SVM, Topic Models.
-Experience in using deep learning frameworks such as tensorflow, cntk, or keras etc.
-Experience in solving NLP problems such as text categorization, text clustering/topic modeling, entity extraction, text summarization etc.
-Experience in monitoring machine learning models in production and in operationalizing model building process.
-Knowledge and experience in supervised and unsupervised algorithms to effectively address business problems.
-Experience in creating interactive data visualizations to create a compelling dashboard of the machine learning model results and performance.
-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, Scala, or Java.
-Experience with distributed databases such as MongoDB, HBase, DynamoDB, Couch base, etc., and good skills in traditional databases such as MS-SQL with T-SQL, SSIS, SSAS or Oracle with PL/SQL, etc.
-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.
-Good knowledge of search engine technologies such as Apache Solr, or Elastic Search and able to define schema, create collections, ingest data into search engine and retrieve data using streaming APIs and graph queries.
-Experience or understanding in AWS SageMaker, Cloudera Data Science Workbench (DSW) or similar ML/DS platform.
-Experience in Cloudera CDH or similar platform with application development skills in Morphline, Flume, Kafka.
-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, or Hue to communicate insights to a wide audience.
-Application development experience with REST API, workflows Oozie, crontabs, and data integration with Sqoop with various data formats Parquet, Avro, Json, etc.
External Referral Bonus:Ineligible
Potential for Telework:No
Clearance Level Required:None
Scheduled Weekly Hours:40
Job Family:Software Development
Leidos is a Fortune 500® information technology, engineering, and science solutions and services leader working to solve the world's toughest challenges in the defense, intelligence, homeland security, civil, and health markets. The company's 33,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Virginia, Leidos reported annual revenues of approximately $10.19 billion for the fiscal year ended December 28, 2018. For more information, visit www.Leidos.com.
Pay and Benefits
Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available here.
Securing Your Data
Leidos will never ask you to provide payment-related information at any part of the employment application process. And Leidos will communicate with you only through emails that are sent from a Leidos.com email address. If you receive an email purporting to be from Leidos that asks for payment-related information or any other personal information, please report the email to [email protected].
Commitment to Diversity
All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.