Job Description

Our client is seeking for a highly skilled and innovative Java Developer with a strong background in artificial intelligence (AI) and machine learning (ML) to join their team. The ideal candidate will be responsible for designing, developing, and implementing robust backend systems that integrate AI and ML models to solve complex business challenges. This role requires deep expertise in the Java ecosystem, experience with AI frameworks, and a passion for building intelligent, data-driven applications.

The position is long term contract and Hybrid (3-4 days a week onsite in Pleasanton CA).

Responsibilities

• Design and develop high-performance, scalable, and secure backend applications and APIs using Java and the Spring framework.
• Integrate and deploy AI and machine learning models into production applications, working closely with data scientists and MLOps teams.
• Implement AI-powered features such as predictive analytics, recommendation engines, natural language processing (NLP), or computer vision.
• Collaborate with cross-functional teams, including data science, product management, and other software engineers, to define project requirements and deliver high-impact features.
• Optimize application performance and troubleshoot issues across distributed systems.
• Develop and maintain data pipelines and processes for AI model training and inference.
• Utilize modern CI/CD practices and containerization technologies (Docker, Kubernetes) for application deployment.
• Stay current with emerging trends and advancements in AI/ML and Java technologies.
• Participate in code reviews and contribute to architectural decisions to maintain high-quality code standards.

Required skills and qualifications

• Education: Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• Experience: Proven experience as a Java Developer with a track record of developing enterprise-level applications.
• Java expertise: Strong proficiency in Java, including hands-on experience with the Spring framework (Spring Boot, Spring AI).
• AI/ML fundamentals: Solid understanding of machine learning algorithms, deep learning, and neural networks.
• AI frameworks: Familiarity with AI frameworks such as Deeplearning4j, TensorFlow, or ONNX.
• Data handling: Experience with SQL/NoSQL databases and data processing techniques.
• Cloud platforms: Knowledge of cloud platforms like AWS, GCP, or Azure and experience deploying applications in a cloud-native environment.

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