AI/ML Engineer

Job Title: AI/ML Engineer

Job Location: Fremont, CA | 5 days onsite

Description:
AgreeYa is a global Systems Integrator seeking an experienced AI/ML Engineer to join the factory software machine learning and computer vision team in Fremont, CA. This role requires a skilled professional to design, develop, and implement critical machine learning models that operate in factory and warehouse environments, solving complex operational problems using diverse, high-volume data.

The AI/ML Engineer will take ambiguous problem statements and build end-to-end models using techniques such as supervised learning, convolutional neural networks, and modern deep learning frameworks like PyTorch, Jax, or TensorFlow, along with Python-based data tooling such as Pandas. The role will partner closely with production, process, controls, and quality teams to deliver robust, scalable solutions and will own models in production, including monitoring and alerting to rapidly address issues.

This position requires working with heterogeneous and multi-modal data, including images, multi-spectral sensor outputs, voice, text, and tabular data, and building sustainable, modular code to transition research concepts into reliable production systems. The ideal candidate is passionate about clean code, rigorous experimentation, and applying statistical principles to compare models and assess solution feasibility and performance.

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.

AgreeYa is a global systems integrator delivering competitive advantage for its customers through software, solutions, and services. Established in 1999, AgreeYa is headquartered in Folsom, California, with a global footprint and a team of more than 2,200 staff across offices. AgreeYa works with 500 organizations ranging from Fortune 100 firms to small and large businesses across industries such as Telecom, Banking, Financial Services & Insurance, Healthcare, Utility & Energy, Technology, Public sector, Pharma & Biotech, and others.

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.