90 applicants

Company

Original Job Post

BTI360 · 3 days ago

Machine Learning Engineer

Herndon, VA

Full-time

Onsite

Mid Level

3+ years exp

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Information TechnologySoftware

Growth Opportunities

Hiring Manager

Debora C. Majors

Insider Connection @BTI360

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Responsibilities

Support the team in building systems to catalog, evaluate, monitor, and publish new ML capabilities.

Work on a high-performance development team to build a platform enabling users and systems to leverage AI/ML capabilities.

Collaborate with the team to transform the way the company's Sponsor does business by expanding AI/ML expertise.

Demonstrate a strong desire to learn, make an impact, and play a crucial role in the development of AI/ML capabilities.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

PythonJavaDjangoFlaskSpring BootCloud ComputingAWSGoogle CloudAzureFull-Stack DevelopmentWeb App DevelopmentInfrastructureDevOpsAWS ServicesRDBMSMySQLPostgreSQLNoSQLDynamoDBMongoDBCI/CD AutomationJenkinsGitOpsCodePipelineAWS Cloud CertifiedFrontend FrameworksKubernetesGenerative AI TechnologiesMLOPs PlatformsData Analysis

Required

2+ years of experience as a software engineer or data scientist with 3-5 years of overall experience

Bachelor’s degree in computer science, Computer Engineering, or Data Science

Ability to develop and maintain basic web applications and experience with frameworks such as Django, Flask, or Spring Boot

Proficient in Python and Java

Proficient in cloud computing platforms such as AWS, Google Cloud, Azure

Comfortable and willing to work and pivot into a variety of roles that may include as a full-stack engineer: web app development, infrastructure, and devops.

Familiarity with the AWS ecosystem of services (i.e., S3, RDS, DynamoDB, Lambda, Glue, Lake Formation, EKS, CloudWatch, SNS/SQS, Sagemaker)

Knowledge of relational database management systems (RDBMS) like MySQL or PostgreSQL, and knowledge of NoSQL dbs such as DynamoDB or MongoDB

Familiarity with CI/CD automation tools such as Jenkins, GitOps, CodePipeline

US Citizen

Preferred

AWS Cloud Certified (i.e., Cloud Practitioner, Solutions Architect, etc.)

Competency with modern frontend frameworks such as Angular, React, Vue

Experience using Kubernetes or other container orchestration tools.

Experience utilizing the latest Generative AI Technologies

Experience with MLOPs platforms (e.g., Kubeflow, Metaflow, mlflow, Flyte)

Experience with data manipulation, analysis, and visualization libraries (pandas, numpy, matplotlib, scikit-learn).

Experience building ML/AI capabilities to solve NLP problems (e.g., text classification, text summarization, named entity recognition, sentiment analysis)

Professional experience working with Large Language Models (LLMs) - prompt engineering, prompt chaining, retrieval-augmented generation (RAG), hallucination mitigation.