Software Engineer Machine Learning Java
Software Engineer Machine Learning Java
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
Job Title: Software Engineer Machine Learning & Java
Location: Sunnyvale CA
Employment Type: C2C/W2
We are seeking a highly skilled Software Engineer with expertise in Machine Learning (ML) Natural Language Processing (NLP) Java Spark SQL and Python. The ideal candidate will design develop and deploy scalable ML models working with large datasets and realtime processing frameworks to build intelligent applications.
Key Responsibilities:- Develop optimize and deploy Machine Learning models for realworld applications.
- Design and implement data pipelines using Spark and other big data technologies.
- Work with NLP techniques for text processing sentiment analysis and chatbot development.
- Implement Javabased backend solutions to integrate ML models into production systems.
- Write and optimize SQL queries for data extraction transformation and analysis.
- Use Python for ML model development data preprocessing and automation.
- Collaborate with data scientists engineers and product teams to deliver scalable AIdriven solutions.
- Optimize model performance and ensure efficient deployment in cloud or onpremise environments.
- Research and implement the latest advancements in ML and AI.
- 8 years of experience in software development with a focus on Machine Learning & Java.
- Handson experience with NLP deep learning frameworks (TensorFlow/PyTorch) and Spark.
- Strong knowledge of SQL database management and distributed computing.
- Proficiency in Python and Java for building and deploying ML models.
- Experience in designing scalable data processing systems.
- Familiarity with cloud platforms (AWS GCP or Azure) is a plus.
- Strong problemsolving and analytical skills.
- Excellent communication and teamwork abilities.
- Experience in realtime ML model deployment.
- Knowledge of Kubernetes Docker or other containerization tools.
- Understanding of MLOps best practices for continuous deployment of ML models.
Employment Type
Full Time
