Role: Machine Learning Engineer
Location: Fremont CA
once the documents are verified a Codility assessment will be shared with the candidate where they need to score a minimum of 70% and post that a general video screening with PV. Then we send the submission to the client
About the Role:
Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design develop and implement critical machine learning models supporting factory and warehouse operations. You will transform ambiguous problem statements into robust end-to-end solutions using a variety of machine learning techniques and tools including supervised learning convolutional neural networks and modern frameworks such as PyTorch and Pandas.
You will collaborate closely with partners in production process controls and quality to deliver solutions for the most challenging problems in our operations. Your work will involve evaluating and deploying models in production environments ensuring rapid and reliable alerting systems and addressing operational issues as they arise. You must be adept at handling diverse heterogeneous datasets that span multiple modalities including images multi-spectral sensor outputs voice text and tabular data.
Responsibilities
- Design develop and deploy machine learning models for factory and warehouse environments.
- Collaborate with cross-functional teams to identify define and solve high-impact operational challenges.
- Build and maintain end-to-end machine learning pipelines from data collection and preprocessing to model deployment and monitoring.
- Evaluate and compare models using statistical methods to ensure optimal performance and feasibility.
- Ensure robust alerting and monitoring systems are in place for deployed models to address issues rapidly.
- Work with diverse datasets integrating multiple data types such as images sensor data voice text and tabular information.
- Write clean modular and sustainable code to translate research ideas into production-ready solutions.
Minimum Requirements
- In-depth knowledge of Python for high-performance data-intensive applications.
- Proficiency with at least one modern deep learning framework (e.g. PyTorch Jax TensorFlow).
- Expertise in one or more of the following areas: computer vision large language models recommender systems or operations research.
- Foundational knowledge of statistics for model comparison and performance assessment.
- Real-world experience deploying and maintaining machine learning solutions in production environments.
- Passion for clean sustainable and modular code to bring research concepts to practical implementation.
Preferred Qualifications
- CI/CD Kubernetes MLflow TensorFlow PyTorch AWS.
- Experience working in manufacturing industrial automation or warehouse environments.
- Familiarity with multi-modal data integration and analysis.
- Strong problem-solving skills and the ability to thrive in ambiguous fast-paced settings.
- Excellent communication skills for cross-functional teamwork.
Role: Machine Learning Engineer Location: Fremont CA once the documents are verified a Codility assessment will be shared with the candidate where they need to score a minimum of 70% and post that a general video screening with PV. Then we send the submission to the client About the Role: Ou...
Role: Machine Learning Engineer
Location: Fremont CA
once the documents are verified a Codility assessment will be shared with the candidate where they need to score a minimum of 70% and post that a general video screening with PV. Then we send the submission to the client
About the Role:
Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design develop and implement critical machine learning models supporting factory and warehouse operations. You will transform ambiguous problem statements into robust end-to-end solutions using a variety of machine learning techniques and tools including supervised learning convolutional neural networks and modern frameworks such as PyTorch and Pandas.
You will collaborate closely with partners in production process controls and quality to deliver solutions for the most challenging problems in our operations. Your work will involve evaluating and deploying models in production environments ensuring rapid and reliable alerting systems and addressing operational issues as they arise. You must be adept at handling diverse heterogeneous datasets that span multiple modalities including images multi-spectral sensor outputs voice text and tabular data.
Responsibilities
- Design develop and deploy machine learning models for factory and warehouse environments.
- Collaborate with cross-functional teams to identify define and solve high-impact operational challenges.
- Build and maintain end-to-end machine learning pipelines from data collection and preprocessing to model deployment and monitoring.
- Evaluate and compare models using statistical methods to ensure optimal performance and feasibility.
- Ensure robust alerting and monitoring systems are in place for deployed models to address issues rapidly.
- Work with diverse datasets integrating multiple data types such as images sensor data voice text and tabular information.
- Write clean modular and sustainable code to translate research ideas into production-ready solutions.
Minimum Requirements
- In-depth knowledge of Python for high-performance data-intensive applications.
- Proficiency with at least one modern deep learning framework (e.g. PyTorch Jax TensorFlow).
- Expertise in one or more of the following areas: computer vision large language models recommender systems or operations research.
- Foundational knowledge of statistics for model comparison and performance assessment.
- Real-world experience deploying and maintaining machine learning solutions in production environments.
- Passion for clean sustainable and modular code to bring research concepts to practical implementation.
Preferred Qualifications
- CI/CD Kubernetes MLflow TensorFlow PyTorch AWS.
- Experience working in manufacturing industrial automation or warehouse environments.
- Familiarity with multi-modal data integration and analysis.
- Strong problem-solving skills and the ability to thrive in ambiguous fast-paced settings.
- Excellent communication skills for cross-functional teamwork.
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