Machine Learning/Deep Learning Operations Engineer

About Terminal

Terminal is a B2B technology company who are dedicated to building software that digitizes, automates, and optimizes logistics spaces by leveraging best-in-class machine learning. Our platform will provide warehouse operators with the intelligence needed to optimize their usage of transportation. We address many industry-wide pain points, from compliance, to phantom costs. These are the fundamental operating assets of the commerce network - and represent the last great frontier of untapped data in logistics. Ultimately, Terminal will become the central platform for the logistics network, seamlessly connecting all datasources to support a wide range of essential functions.

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Position overview

Terminal is in search of a Senior MLOps Engineer with a passion for automating and streamlining ML workflows. At Terminal, you'll be a linchpin in crafting, optimizing, and delivering machine learning models efficiently and at scale.You will drive the forefront of ML experiment tracking, spearhead model optimization processes, and ensure seamless integrations with data operations.Your insights will be indispensable in implementing automation solutions that bolster model quality, expedited through rigorous evaluation and feedback loops. By actively participating in architectural discussions, you will helpshape the direction and future of our machine learning operations and infrastructure

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Responsibilities

• Designing, implementing and operating automated pipelinesfor ML model training, retraining, and optimisation
• Conducting ML model testing and evaluating systemperformance
• Handling ML model release, deployment and delivery
• Providing guidelines and mentorship to other team members on ML model optimisation and delivery

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Requirement

• Degree in Machine Learning, Artificial Intelligence, DataScience, Computer Science, Mathematics, or a similar field
• At least 5 years of experience working as a MachineLearning/Deep Learning Engineer
• Strong proficiency in Python.
• Extensive knowledge of Machine Learning/Deep Learning frameworks, libraries, data structures, data modeling, and software architecture
• Experience working with at least one MLOps platform e.g.,Amazon SageMaker, ClearML, Weights & Biases, as well as experience in deploying ML models to a cloud platform
• Superb analytical and problem-solving abilities
• Great communication and collaboration skills
• Excellent time management and organizational abilities

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Desirable

• Proficiency with C++, particularly for ML optimisation and/or computer vision e.g., Nvidia TensorRT or Intel OpenVINO, is advantageous
• Start-up experience beneficial
• Knowledge of AWS

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Benefits

• Competitive Pay
• Health Insurance
• Critical illness, Income protection and Life Insurance
• Pension
• Meal allowance
• Hybrid working