Machine Learning Engineer 3 - Contract - TalentBurst, Inc.
Sunnyvale, CA
About the Job
Job Title: Machine Learning Engineer 3
Job Location: Sunnyvale, CA -Onsite - Hybrid
Location: 12 Months
W2 Preferred (No Sponsorship required)
Primary Function of Position
The Machine Learning Engineer is responsible for designing, developing, and deploying AI/ML applications
at scale.
The role focuses on architecting robust systems for AI/ML workflows, building scalable data
pipelines, and collaborating with cross-functional teams to integrate AI solutions into existing products.
This position plays a key role in developing APIs, optimizing application performance, and ensuring the seamless deployment of models in production environments.
Essential Job Duties
Design, develop, and deploy end-to-end AI/ML applications at scale
Architect robust and scalable systems for AI/ML workflows
Build and maintain scalable data pipelines and infrastructure to support AI/ML operations
Collaborate with cross-functional teams to integrate AI/ML solutions into existing products
Develop and implement APIs to enable communication between machine learning models and other systems
Optimize the performance of AI/ML applications through testing, tuning, and profiling
Ensure the smooth deployment of AI/ML models by integrating continuous
integration/continuous deployment (CI/CD) pipelines
Required Skills and Experience
5+ years of professional experience building end-to-end AI/ML applications
Strong system design skills with experience architecting complex, scalable AI/ML systems
Strong software engineering skills with proficiency in Python and/or C++/C/Java
Knowledge of DevOps practices and CI/CD pipelines
Experience with machine learning frameworks such as TensorFlow or PyTorch
Experience with distributed systems
Solid understanding of data structures, algorithms, and software design principles
Expertise in MLOps practices, tools, and workflows
Experience in integrating AI/ML models into production
environments with performance monitoring and version control
Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and
containerization technologies
Required Education and Training
Bachelor's degree in Computer Science, Engineering, or related field; Master's or PhD preferred
Working Conditions
Preferred Skills and Experience
Familiarity with Generative AI models and techniques
Experience with chatbot development, particularly using RAG techniques or similar.
Contributions to open-source ML projects
Knowledge of DevOps practices and CI/CD pipelines
#TB_EN
Job Location: Sunnyvale, CA -Onsite - Hybrid
Location: 12 Months
W2 Preferred (No Sponsorship required)
Primary Function of Position
The Machine Learning Engineer is responsible for designing, developing, and deploying AI/ML applications
at scale.
The role focuses on architecting robust systems for AI/ML workflows, building scalable data
pipelines, and collaborating with cross-functional teams to integrate AI solutions into existing products.
This position plays a key role in developing APIs, optimizing application performance, and ensuring the seamless deployment of models in production environments.
Essential Job Duties
Design, develop, and deploy end-to-end AI/ML applications at scale
Architect robust and scalable systems for AI/ML workflows
Build and maintain scalable data pipelines and infrastructure to support AI/ML operations
Collaborate with cross-functional teams to integrate AI/ML solutions into existing products
Develop and implement APIs to enable communication between machine learning models and other systems
Optimize the performance of AI/ML applications through testing, tuning, and profiling
Ensure the smooth deployment of AI/ML models by integrating continuous
integration/continuous deployment (CI/CD) pipelines
Required Skills and Experience
5+ years of professional experience building end-to-end AI/ML applications
Strong system design skills with experience architecting complex, scalable AI/ML systems
Strong software engineering skills with proficiency in Python and/or C++/C/Java
Knowledge of DevOps practices and CI/CD pipelines
Experience with machine learning frameworks such as TensorFlow or PyTorch
Experience with distributed systems
Solid understanding of data structures, algorithms, and software design principles
Expertise in MLOps practices, tools, and workflows
Experience in integrating AI/ML models into production
environments with performance monitoring and version control
Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and
containerization technologies
Required Education and Training
Bachelor's degree in Computer Science, Engineering, or related field; Master's or PhD preferred
Working Conditions
Preferred Skills and Experience
Familiarity with Generative AI models and techniques
Experience with chatbot development, particularly using RAG techniques or similar.
Contributions to open-source ML projects
Knowledge of DevOps practices and CI/CD pipelines
#TB_EN
Source : TalentBurst, Inc.