MLOps Engineer

Overview

Hybrid
Depends on Experience
Contract - W2
Contract - 12 Month(s)

Skills

Java
NLP
Spring
Hibernate
NoSQL
TensorFlow
Docker

Job Details

Title: Java with Gen AI
Location: Irving, TX (Hybrid)

The Role
Responsibilities:
Design, develop, and maintain scalable Java backend applications, ensuring high performance and responsiveness.
Implement Generative AI solutions, including natural language processing (NLP) and machine learning algorithms, to enhance business functionalities.
Collaborate with data scientists and other stakeholders to integrate AI models into existing systems and applications.
Analyze and optimize performance of AI-driven solutions, ensuring they meet operational requirements.
Participate in the full software development lifecycle (SDLC), including requirements gathering, design, development, testing, and deployment.
Write clean, maintainable, and efficient code while adhering to software development best practices.
Conduct code reviews, providing constructive feedback to peers and ensuring code quality.
Mentor junior developers, sharing knowledge on Java development and Generative AI applications.
Stay informed about the latest trends and advancements in Generative AI and Java technologies.
Requirements:

Bachelor s degree in computer science, Software Engineering, or a related field.
10+ years of experience in Java development, with a strong focus on backend services.
Proven experience with Generative AI technologies and frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
Strong understanding of natural language processing (NLP) and machine learning concepts.
Proficiency in Java frameworks (e.g., Spring, Hibernate) and development tools (e.g., Maven, Gradle).
Experience with RESTful APIs, microservices architecture, and cloud platforms (e.g., AWS, Azure).
Knowledge of relational databases (e.g., Oracle, MySQL) and NoSQL databases (e.g., MongoDB).
Strong analytical and problem-solving skills with the ability to work independently and collaboratively.
Excellent communication skills, with a knack for explaining complex technical concepts to non-technical stakeholders.
Preferred, but not required:

Experience with containerization technologies (e.g., Docker, Kubernetes).
Familiarity with Agile methodologies and DevOps practices.
Contributions to open-source projects or research in the field of AI will be a plus.

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