Jobs via Dice
Job Title
AI/ML Engineer
Location Fremont, CA
Overview AgreeYa Solutions, a global Systems Integrator, is seeking an experienced AI/ML Engineer to join the factory software machine learning and computer vision team in Fremont, CA. The role requires designing, developing, and implementing critical machine learning models that operate in factory and warehouse environments, solving complex operational problems using diverse high-volume data.
Job Responsibilities
Design, develop, and deploy end-to-end machine learning models for factory and warehouse use‑cases, including data ingestion, feature engineering, training, evaluation, and productionization.
Build and optimize computer vision and/or other ML solutions (e.g., large language models, recommender systems, operations research models) to address high‑impact operational challenges.
Work with cross‑functional stakeholders in production, process, controls, quality, and software engineering to translate ambiguous business problems into well‑defined ML solutions and deliver measurable outcomes.
Implement robust monitoring, logging, and alerting for ML models in production to ensure reliability, performance, and rapid incident response.
Clean, transform, and manage diverse data sets across multiple modalities, ensuring data quality, consistency, and usability for modeling.
Apply foundational statistical methods to design experiments, compare model performance, and validate solution effectiveness before and after deployment.
Write clean, modular, reusable Python code and collaborate in code reviews, architecture discussions, and best practice initiatives for ML engineering.
Required Skills & Experience
In-depth knowledge of Python for high‑performance, data‑intensive applications, including experience with data manipulation libraries (e.g., Pandas, NumPy).
Hands‑on experience with at least one modern deep learning framework such as PyTorch, Jax, or TensorFlow, including training, tuning, and deploying models.
Expertise in one or more domains such as computer vision, large language models, recommender systems, or operations research.
Foundational knowledge of statistics for model comparison, hypothesis testing, and assessing solution feasibility and performance.
Proven experience deploying and maintaining production machine learning use‑cases, including monitoring, troubleshooting, and lifecycle management.
Passion for clean code, sustainable modular design, and taking research prototypes into robust production systems.
Preferred Skills & Experience
Experience working with multi‑modal data (images, sensor data, text, voice, tabular) in industrial, manufacturing, or warehouse environments.
Exposure to distributed systems, real‑time data processing, or control/monitoring applications supporting operations.
Familiarity with cloud platforms (Azure, AWS, or Google Cloud Platform) for deploying and managing ML workloads, services, or containers.
Experience with performance tuning and optimization of ML pipelines, including model inference performance, resource utilization, and data pipeline efficiency.
Education Required
Bachelor’s degree in Computer Science, Data Science, Electrical/Computer Engineering, Mathematics, or a related technical field, or equivalent practical experience.
Equal Opportunity Employer Statement AgreeYa is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, gender identity, sexual orientation, national origin, disability, veteran status, or other protected characteristics.
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Location Fremont, CA
Overview AgreeYa Solutions, a global Systems Integrator, is seeking an experienced AI/ML Engineer to join the factory software machine learning and computer vision team in Fremont, CA. The role requires designing, developing, and implementing critical machine learning models that operate in factory and warehouse environments, solving complex operational problems using diverse high-volume data.
Job Responsibilities
Design, develop, and deploy end-to-end machine learning models for factory and warehouse use‑cases, including data ingestion, feature engineering, training, evaluation, and productionization.
Build and optimize computer vision and/or other ML solutions (e.g., large language models, recommender systems, operations research models) to address high‑impact operational challenges.
Work with cross‑functional stakeholders in production, process, controls, quality, and software engineering to translate ambiguous business problems into well‑defined ML solutions and deliver measurable outcomes.
Implement robust monitoring, logging, and alerting for ML models in production to ensure reliability, performance, and rapid incident response.
Clean, transform, and manage diverse data sets across multiple modalities, ensuring data quality, consistency, and usability for modeling.
Apply foundational statistical methods to design experiments, compare model performance, and validate solution effectiveness before and after deployment.
Write clean, modular, reusable Python code and collaborate in code reviews, architecture discussions, and best practice initiatives for ML engineering.
Required Skills & Experience
In-depth knowledge of Python for high‑performance, data‑intensive applications, including experience with data manipulation libraries (e.g., Pandas, NumPy).
Hands‑on experience with at least one modern deep learning framework such as PyTorch, Jax, or TensorFlow, including training, tuning, and deploying models.
Expertise in one or more domains such as computer vision, large language models, recommender systems, or operations research.
Foundational knowledge of statistics for model comparison, hypothesis testing, and assessing solution feasibility and performance.
Proven experience deploying and maintaining production machine learning use‑cases, including monitoring, troubleshooting, and lifecycle management.
Passion for clean code, sustainable modular design, and taking research prototypes into robust production systems.
Preferred Skills & Experience
Experience working with multi‑modal data (images, sensor data, text, voice, tabular) in industrial, manufacturing, or warehouse environments.
Exposure to distributed systems, real‑time data processing, or control/monitoring applications supporting operations.
Familiarity with cloud platforms (Azure, AWS, or Google Cloud Platform) for deploying and managing ML workloads, services, or containers.
Experience with performance tuning and optimization of ML pipelines, including model inference performance, resource utilization, and data pipeline efficiency.
Education Required
Bachelor’s degree in Computer Science, Data Science, Electrical/Computer Engineering, Mathematics, or a related technical field, or equivalent practical experience.
Equal Opportunity Employer Statement AgreeYa is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, gender identity, sexual orientation, national origin, disability, veteran status, or other protected characteristics.
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