Machine Learning Engineer

Enexus Global
Fremont, CA, United States
2 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Clean Code Principles Computer Vision Big Data Data Transformation Python (Programming Language) Machine Learning Recommender Systems Tensorflow Supervised Learning Data Processing Data Ingestion Pytorch
+5 more
Large Language Models Deep Learning Model Validation Integration Frameworks Machine Learning Operations

Job description

Our direct client is seeking a highly skilled Machine Learning Engineer to join their Software Machine Learning and Computer Vision team. In this role, you will be responsible for designing, developing, and deploying advanced machine learning solutions that support factory and warehouse operations. You will transform complex and ambiguous business challenges into scalable, end-to-end solutions using a variety of machine learning techniques, including supervised learning, computer vision, and deep learning frameworks such as PyTorch. The ideal candidate will collaborate closely with cross-functional teams across Production, Process Engineering, Controls, and Quality to address critical operational challenges. This position requires hands-on experience with model development, deployment, monitoring, and maintenance in production environments, as well as the ability to work with diverse and multi-modal datasets, including images, sensor data, voice, text, and structured data., * Design, develop, and deploy machine learning models to enhance factory and warehouse operations.

  • Partner with cross-functional stakeholders to identify and solve high-impact operational challenges.
  • Build and maintain end-to-end machine learning pipelines, including data ingestion, preprocessing, model training, deployment, and monitoring.
  • Evaluate and benchmark machine learning models using statistical methodologies to ensure optimal performance and business value.
  • Develop robust monitoring and alerting mechanisms to ensure reliability and rapid issue resolution for production models.
  • Integrate and analyze heterogeneous datasets, including image data, sensor outputs, voice recordings, text, and tabular datasets.
  • Write clean, scalable, and maintainable code to translate research concepts into production-ready solutions.

Requirements

  • Strong proficiency in Python, particularly for high-performance and data-intensive applications.
  • Hands-on experience with at least one modern deep learning framework, such as PyTorch, JAX, or TensorFlow.
  • Expertise in one or more of the following domains:
  • Computer Vision
  • Large Language Models (LLMs)
  • Recommender Systems
  • Operations Research
  • Solid understanding of statistics and experimental methods for model evaluation and comparison.
  • Proven experience deploying, monitoring, and maintaining machine learning solutions in production environments.
  • Strong commitment to writing clean, modular, and sustainable code., * Experience working within manufacturing, industrial automation, logistics, or warehouse environments.
  • Familiarity with multi-modal data processing and integration techniques.
  • Strong analytical and problem-solving abilities with the capacity to thrive in fast-paced and ambiguous environments.
  • Excellent communication and collaboration skills, with the ability to work effectively across cross-functional teams.

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Good distractions

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