Staff Software Engineer

4 days ago

Silver Spring, Maryland, United States eSimplicity Full time
About eSimplicity

eSimplicity is a leading digital services company that delivers innovative federal and commercial IT solutions designed to improve the health and lives of millions of Americans while defending our national interests.

We specialize in transforming government services through cutting-edge technologies, leveraging our team's experience in various federal civilian customers on diverse projects across our core competencies.

Job Summary

We are seeking a highly skilled Staff Software Engineer to join our team and help deploy groundbreaking technical solutions to solve our customers' hardest problems. As a key member of our team, you will work with Machine Learning Engineers and Data Scientists to build, scale, and maintain AI/ML training and scoring pipelines.

You will be responsible for ensuring the pipelines track data lineage and promote explainability, while also supporting assessment and research of incorporating AI-DevOps and AI-ops into our infrastructure.

Key Responsibilities
  • Implementing Large-Scale Data Ecosystems

Design and implement large-scale data ecosystems, including data management, governance, and integration of structured and unstructured data to generate insights leveraging cloud-based platforms.

Developing End-to-End Ops Pipelines

Develop end-to-end (Data/Dev/ML) Ops pipelines based on in-depth understanding of cloud platforms, AI lifecycle, and business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably.

Operationalizing and Monitoring ML Models

Operationalize and monitor ML models using high-end tools and technologies, ensuring seamless integration with our cloud infrastructure.

Maintaining Current Data Product APIs

Maintain current data product APIs, releasing ML models on a regular cadence, building capability of continuous training and monitoring.

Explaining Model Behaviour/Results

Explain model behavior/results to both technical and non-technical audiences, ensuring effective communication and collaboration.

Understanding Customer Requirements

Understand customer requirements and project KPIs, ensuring alignment with business objectives.

Implementing Development, Testing, and Automation Tools

Implement various development, testing, automation tools, and IT infrastructure, ensuring seamless integration with our cloud ecosystem.

Defining and Setting Development Processes

Define and set development, test, release, update, and support processes for DevOps operation, ensuring efficient and predictable delivery.

Troubleshooting and Code Review

Troubleshoot techniques and fix code bugs, ensuring high-quality code and adherence to best practices.

Monitoring Processes and Improving Efficiency

Monitor processes during the entire lifecycle for its adherence and updating or creating new processes for improvement and minimizing wastage.

Encouraging Automated Processes

Encourage and build automated processes wherever possible, ensuring efficient and scalable solutions.

Participating in Incidence Management

Participate in incidence management and root cause analyses, ensuring prompt resolution and continuous improvement.

Coordinating and Communicating with the Team

Coordinate and communicate within the team and with customers, ensuring effective collaboration and project delivery.

Selecting and Deploying CI/CD Tools

Select and deploy appropriate CI/CD tools, ensuring seamless integration with our cloud infrastructure.

Striving for Continuous Improvement

Strive for continuous improvement and build continuous integration, continuous development, and constant deployment pipeline (CI/CD Pipeline), ensuring efficient and predictable delivery.

Requirements
  • Bachelor's Degree or Equivalent

Bachelor's Degree or equivalent in experience in Engineering, Computer Science, or related field.

10+ Years of Experience

10+ years working in software development, preferably related to ML or Data Science.

Extensive Experience in AWS Cloud

Extensive experience in AWS cloud data architecture and big data technologies, including EMR, Databricks, Hive, Spark, AWS Glue, Athena, and Redshift.

Experience Working in AWS

Experience working in AWS, including experience with AWS services and frameworks.

Experience Working on Linux-Based Infrastructure

Experience working on Linux-based infrastructure, including experience with IaC tools such as Terraform, Ansible, and AWS CloudFormation.

Experience Setting Up AuthN and AuthZ Systems

Experience setting up AuthN and AuthZ systems, including Active Directory, Okta, and AWS IAM Policies/Roles using attribute-based access controls.

Strong Experience with Python and PySpark

Strong experience with Python, PySpark, R, RStudio, and SageMaker.

Experience Configuring and Managing Databases

Experience configuring and managing databases such as Hive, MySQL, MongoDB.

Experience with Docker, ECS, and EKS

Experience with Docker, ECS, and EKS.

Familiarity with Data Mining and AI/ML Libraries

Familiarity with data mining, supervised, and unsupervised learning methodologies including data dimensionality reduction, correlation analysis, linear regression, PCA, clustering, random forest, etc. Familiarity with AI/ML libraries such as scikit-learn, SparkML, TensorFlow, PyTorch.

Excellent Troubleshooting Skills

Excellent troubleshooting skills, with the ability to analyze complex problems and develop effective solutions.

Working Knowledge of Various Tools and Technologies

Working knowledge of various tools, open-source technologies, and cloud services.

Awareness of Critical Concepts in Security, DevOps, and Agile Principles

Awareness of critical concepts in Security, DevOps, and Agile principles, with the ability to apply them in a real-world setting.

Desired Qualifications
  • Experience with Configuring LLMs on Bedrock

Experience with configuring LLMs on Bedrock.

Experience with Retrieval-Augmented Generation (RAG) for LLMs in AWS Bedrock

Experience with Retrieval-Augmented Generation (RAG) for LLMs in AWS Bedrock.

Experience with Amazon Aurora PostgreSQL

Experience with Amazon Aurora PostgreSQL.

Experience with Amazon Kendra

Experience with Amazon Kendra.

Experience with Agents and Mixture-of-Experts (MoE) in LLMs

Experience with agents and mixture-of-experts (MoE) in LLMs.

Experience with Amazon SageMaker ML Lineage Tracking

Experience with Amazon SageMaker ML Lineage Tracking.

AWS Machine Learning Specialization Certification

AWS Machine Learning Specialization Certification.

Working Environment

This program supports a remote work environment operating within the Eastern time zone, allowing us to work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by your manager.

Occasional travel for training and project meetings is estimated to be less than 25% per year.

Benefits

We offer a highly competitive salary, healthcare benefits, and a flexible leave policy.

Equal Employment Opportunity

eSimplicity is an equal-opportunity employer. All qualified applicants will be considered for employment without regard to race, religion, color, national origin, gender, age, status as a protected veteran, sexual orientation, gender identity, or status as a qualified individual with a disability.

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