Machine Learning Engineer

Company: Aerotek
Location: Manassas
Posted on: April 10, 2021

Job Description:

Description:Primary Duties/Responsibilities: The ideal candidate will bring in-depth experience in the development and deployment of AI/ML models and products for commercial and/or government customers. This candidate will work individually or lead small teams to define customer needs, collect and clean data, design/train/test models, and configure and refine local and cloud-based ML pipelines for model training and serving. The candidate will participate in cross-domain working groups to coordinate development and deployment efforts, briefing results to senior engineers and managers in government and industry. This position requires an imaginative thinker with experience across a wide range of ML approaches to be able to identify strategies that meet both the mission needs and operational constraints. Development and deployment environments for AI/ML models will require use of VM or containerized approaches. The candidate must be a motivated self-starter who thrives with limited supervision.Required Qualifications/Skills/Abilities: -BS/MS degree in Computer Engineering, Computer Science, Software Engineering or related field with 5+ years of related AI/ML experience-Experience in a wide range of AI/ML techniques (including deep learning) and libraries such as tensorflow, pytorch, and keras-Experience with local and cloud-based ML platforms (e.g. AWS Sagemaker, GCP)-Highly proficient in Python, C/C++, shell scripting-Experience with ML pipeline tools and MLOps (including data and pipeline versioning, run orchestration, experiment tracking, hyperparameter tuning, and model serving and monitoring) such as DVC, Pachyderm, Kubeflow, Airflow, MLflow, and Cortex-Proficient with modern PaaS environment tools such as Kubernetes, docker, KVM, and Helm--Articulate, excellent presentation skills-US Citizen with current SECRET Clearance or ability to obtain a SECRET clearance-Successful completion of background checkSkills:c++, python, machine learning, scripting, kubernetes, docker containers, docker, c/c++, tensorflowTop Skills Details:Machine Learning Artificial IntelligenceKubernetesAdditional Skills & Qualifications:Desired Qualifications/Skills/Abilities: Prior experience with US Navy tactical/weapon systems is desirablePrior experience training or serving models for Edge AIFamiliar with cybersecurity aspects of ML development and deploymentFamiliar with Agile software development methodology, JIRAFamiliar with model-based software/systems engineering conceptsProject Description: SWFTS program. They are working on submarine architecture aspects to provide insights in AI/ML to submarines and train the systems deploy the AI/ML algorithm's to underwater systems and sonars.They are looking for someone with prior product experience in the DoD, someone who has background in algorithm development and coding. This role is based out of manassas but has work from home flexibility during covid.Experience Level:Intermediate Level About Aerotek:We know that a company's success starts with its employees. We also know that an individual's success starts with the right career opportunity. As a Best of Staffing Client and Talent leader, Aerotek's people-focused approach yields competitive advantage for our clients and rewarding careers for our contract employees. Since 1983, Aerotek has grown to become a leader in recruiting and staffing services. With more than 250 non-franchised offices, Aerotek's 8,000 internal employees serve more than 300,000 contract employees and 18,000 clients every year. Aerotek is an Allegis Group company, the global leader in talent solutions. Learn more at Aerotek.com.The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.

Keywords: Aerotek, Alexandria , Machine Learning Engineer, Engineering , Manassas, Virginia