Machine Learning Engineer Chantilly, VA · Full-time apply →

Kraken Networks, Inc.; Chantilly, Northern (VA, KY); Hybride; USD 140 000 - 200 000; Plein temps

Résumé du poste

Kraken Networks, Inc. is seeking a Software Developer with expertise in artificial intelligence to join its dynamic team in Chantilly, VA.

The role centers on developing and implementing AI solutions to strengthen enterprise-level IT operations. The Machine Learning Engineer will collaborate with cross-functional teams to design, develop, and deploy AI-driven applications that enhance efficiency, automate processes, and deliver valuable insights.

Qualifications

• Bachelor’s degree in CS, software engineering, data science, or related field.
• Five years of professional software development or ML engineering experience.
• Strong Python, with solid OO, data structures, and algorithms knowledge.
• Experience with Git, Docker, and databases (SQL and/or NoSQL).
• Knowledge of LLM technologies and LangChain/LangGraph orchestration.
• Understanding of retrieval-augmented generation and vector databases.
• Cloud experience (AWS/Azure/GCP) and MLOps practices.
• Excellent problem-solving, communication, and teamwork abilities.

Responsabilités

• Develop and maintain machine learning pipelines and applications using Python and contemporary machine learning frameworks.
• Implement and optimize algorithms for integrating and deploying large language models (LLMs).
• Build RESTful APIs and microservices to serve machine learning models in production environments.
• Write clean, maintainable, and well-documented code, adhering to object-oriented programming principles.
• Collaborate with cross-functional teams to understand requirements and convert them into technical solutions.
• Manage training data, model artifacts, and application state using SQL, NoSQL, and vector databases.
• Containerize machine learning applications with Docker to ensure consistent deployment across environments.
• Use Git for version control and participate in code reviews to maintain code quality.
• Conduct testing and debugging of machine learning applications to ensure reliability and accuracy.
• Support the deployment and monitoring of AI and machine learning models in cloud environments.
• Stay up to date with emerging trends in machine learning, LLMs, and AI engineering best practices.

Connaissances

Python programming

Object-oriented design

Problem-solving

Communication skills

Agile development

Formation

Bachelor’s degree in CS/Software Eng/Data Science

Master’s degree in CS or related field

Outils

Git

Docker

Kubernetes

LangChain

LangGraph

ChromaDB

Pinecone

Weaviate

SQL/NoSQL databases

AWS

Azure

Google Cloud

CI/CD tools

Ansible

ServiceNow

SAP

Tableau

Splunk

Description du poste

Software Developer with expertise in artificial intelligence, developing and implementing AI solutions to strengthen enterprise-level IT operations

We are searching for a Software Developer with expertise in artificial intelligence to join its dynamic team. This position centers on developing and implementing AI solutions to strengthen enterprise-level IT operations. The Machine Learning Engineer will collaborate closely with cross-functional teams to design, develop, and deploy AI-driven applications that enhance efficiency, automate processes, and deliver valuable insights.

Responsibilities

Develop and maintain machine learning pipelines and applications using Python and contemporary machine learning frameworks.

Implement and optimize algorithms for integrating and deploying large language models (LLMs).

Build RESTful APIs and microservices to serve machine learning models in production environments.

Write clean, maintainable, and well-documented code, adhering to object-oriented programming principles.

Collaborate with cross-functional teams to understand requirements and convert them into technical solutions.

Manage training data, model artifacts, and application state using SQL, NoSQL, and vector databases.

Containerize machine learning applications with Docker to ensure consistent deployment across environments.

Use Git for version control and participate in code reviews to maintain code quality.

Conduct testing and debugging of machine learning applications to ensure reliability and accuracy.

Support the deployment and monitoring of AI and machine learning models in cloud environments.

Stay up to date with emerging trends in machine learning, LLMs, and AI engineering best practices.

Qualifications Required

Active TS/SCI clearance with Poly.

Bachelor’s degree in computer science, software engineering, data science, or a related technical field, plus five years of professional experience in software development or machine learning engineering.

Strong proficiency in Python programming, with a thorough understanding of object-oriented programming concepts, design patterns, data structures, and algorithms.

Experience with development tools and practices, including Git version control, Docker containerization, and database management (SQL and/or NoSQL).

Knowledge of large language model technologies, including familiarity with orchestration frameworks such as LangChain and LangGraph.

Understanding of retrieval-augmented generation (RAG) architectures and vector databases (including ChromaDB, Pinecone, Weaviate, or similar) for building intelligent retrieval systems.

Strong problem-solving skills, attention to detail, excellent communication abilities, and eagerness to learn within a collaborative team environment.

Master’s degree in computer science or a related field.

Experience with cloud platforms such as AWS, Azure, or Google Cloud, and knowledge of MLOps practices for machine learning model deployment and monitoring.

Experience with container orchestration and DevOps, including Kubernetes, Rancher, CI/CD pipelines, and infrastructure automation tools like Ansible.

Familiarity with enterprise platforms such as ServiceNow, SAP, Tableau, or Splunk.

Contributions to open-source machine learning projects and familiarity with Agile development methodologies.