Title: Data Scientist / Machine Learning Engineer Location: Reston, VA (Hybrid) Duration: Initial 1 year contract with potential extension Compensation: $85/hour - $92/hour Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S. Skillset / Experience: Leads proliferation of machine learning and artificial intelligence throughout the enterprise. Identifies and solves business problems by using various numerical techniques, algorithms, and models in statistical modeling, machine learning, operations research, and data mining. Uses advanced analytical capabilities to support data science initiatives. Communicates across product teams and with customers and educates on artificial intelligence, machine learning, and statistical models. Leads interactions between analytics, business units and other departments. Essential Functions: 20% Leads all data mining and extraction activities and applies algorithms to derive insights. 15% Synthesizes analytical findings for consumption by the teams and senior executives. 15% Leads proliferation of machine learning and artificial intelligence solutions. 15% Applies artificial intelligence techniques to achieve concrete business goals while managing limited resources and constraints around data. 15% Mentors and develops junior data scientists for advanced data analysis. 10% Translates business priorities and creates data science deliverables. 10% Leads implementation of ML/AI/DS best practices for new data products and builds robust and scalable software. Qualifications: To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Education Level: Bachelor's Degree Education Details: Statistics, Mathematics, Computer Science or related field Experience: 8 years of relevant work experience. In lieu of a Bachelor's degree, an additional 4 years of relevant work experience is required in addition to the required work experience. Preferred Qualifications: Ability to communicate effectively and document objectives and procedures., Expert Ability to leverage a wide variety of data science tools and frameworks., Expert Ability to support data exploration and data analysis tasks in support of analytics objectives., Expert Knowledge in model evaluation, tuning and performance, operationalization, and scalability of scientific techniques., Expert Proficiency in statistical modeling applications., Expert Proficiency in advanced SQL in multiple syntaxes., Expert Proficiency in AWS Ecosystem and tools Experience working as an AI/ML Engineer Our benefits package includes: <ul> <li>Comprehensive medical benefits</li> <li>Competitive pay </li> <li>401(k) retirement plan</li> </ul> <ul> <li>...and much more!</li> </ul> About INSPYR Solutions Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com. INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, INSPYR Solutions complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. 24-07715

Job Description As an MLOps Implementation Engineer, your primary responsibility will be to understand and implement our pre-developed MLOps strategies across various tools, including Domino Data Lab and AWS SageMaker. You will play a crucial role in containerizing these models and developing automated processes to deploy them into AWS Batch, Amazon Elastic Container Registry (ECR), or Amazon Elastic Kubernetes Service (EKS).Additional info :Key Responsibilities:- Interact with Analytics teams to gather requirements for Python and R container images.- Resolve dependencies for the required Python and R packages.- Identify and address any security vulnerabilities in the container images.- Develop and maintain custom container images to ensure compatibility with SageMaker and Domino Data Lab.- Test and validate container images to ensure they meet performance and reliability standards.- Collaborate with cross-functional teams to ensure seamless integration and deployment of custom images.- Document processes and provide training as needed to ensure team members can effectively use and manage the custom containers.Requirements:- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.- Proven experience in managing and developing custom containers, especially with Python and R.- Strong expertise with Amazon SageMaker and its various components.- Experience with containerization technologies such as Docker.- Knowledge of dependency management and package resolution for Python and R.- Understanding of security best practices and vulnerability mitigation for container images.- Familiarity with CI/CD pipelines and tools (e.g., Jenkins, GitLab CI/CD).- Strong programming skills in Python and/or R.- Excellent problem-solving skills and attention to detail.- Strong communication and collaboration skills.Preferred Qualifications:- Experience with AWS Cloud and its services like S3, ECR, EKS etc.· Knowledge of infrastructure as code (IaC) using tools like Terraform or AWS CloudFormation.· Understanding of machine learning model lifecycle management.

MLOps Implementation EngineerFull TimeReston, Virginia As an MLOps Implementation Engineer, your primary responsibility will be to understand and implement our pre-developed MLOps strategies across various tools, including Domino Data Lab and AWS SageMaker. You will play a crucial role in containerizing these models and developing automated processes to deploy them into AWS Batch, Amazon Elastic Container Registry (ECR), or Amazon Elastic Kubernetes Service (EKS).Additional info :Key Responsibilities:- Interact with Analytics teams to gather requirements for Python and R container images.- Resolve dependencies for the required Python and R packages.- Identify and address any security vulnerabilities in the container images.- Develop and maintain custom container images to ensure compatibility with SageMaker and Domino Data Lab.- Test and validate container images to ensure they meet performance and reliability standards.- Collaborate with cross-functional teams to ensure seamless integration and deployment of custom images.- Document processes and provide training as needed to ensure team members can effectively use and manage the custom containers.Requirements:- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.- Proven experience in managing and developing custom containers, especially with Python and R.- Strong expertise with Amazon SageMaker and its various components.- Experience with containerization technologies such as Docker.- Knowledge of dependency management and package resolution for Python and R.- Understanding of security best practices and vulnerability mitigation for container images.- Familiarity with CI/CD pipelines and tools (e.g., Jenkins, GitLab CI/CD).- Strong programming skills in Python and/or R.- Excellent problem-solving skills and attention to detail.- Strong communication and collaboration skills.Preferred Qualifications:- Experience with AWS Cloud and its services like S3, ECR, EKS etc.· Knowledge of infrastructure as code (IaC) using tools like Terraform or AWS CloudFormation.· Understanding of machine learning model lifecycle management.

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Machine Learning Engineer Jobs in Reston, VA

Machine Learning EngineerJuly 23, 2024

Machine Learning EngineerJuly 22, 2024

Senior Machine Learning EngineerJuly 22, 2024

Senior Cyber Software Machine Learning EngineerJuly 16, 2024

Machine Learning EngineerJuly 6, 2024

Machine Learning EngineerJuly 5, 2024