About The Role

Our client, a prominent leader in the hospitality industry, is seeking a skilled and innovative Machine Learning Engineer to join their team. This position offers a unique opportunity to architect and build advanced cloud-based pipelines and machine learning frameworks at scale, driving business transformation through data-driven insights. The ideal candidate will have deep expertise in model design, development, and deployment, coupled with a strong technical foundation in machine learning and data science.

Key Responsibilities

ML Pipeline Architecture: Design and implement robust, scalable cloud-based pipelines to train, deploy, infer, and monitor machine learning models, ensuring the seamless integration of these models into the business’s operations.
Model Design & Evaluation: Leverage expertise in model design, training, evaluation, validation, and implementation to build predictive models and algorithms that align with the organization’s strategic objectives.
Data Management: Conduct data preprocessing, feature engineering, and model evaluation, managing workflows and data pipelines to ensure optimal model performance.
Monitoring & Optimization: Develop and implement monitoring systems to track the performance of machine learning models, making adjustments as necessary to maintain accuracy and efficiency.
Exploratory Analysis: Conduct in-depth exploratory and descriptive data analysis, utilizing large datasets to identify trends, patterns, and opportunities for business improvement. Apply visualization techniques to convey insights clearly to non-technical stakeholders.
Infrastructure & Best Practices: Make informed infrastructure decisions based on a deep understanding of ML modeling techniques, including model choice, data selection, and hyperparameter tuning. Ensure all code is well-managed and models are governed according to best practices in Responsible and Explainable AI.
Technical Leadership: Provide mentorship and technical guidance to other team members, driving code reviews and adherence to best practices. Stay current with the latest research and technologies in the ML engineering community, fostering innovation within the team.
Documentation & Governance: Create and maintain detailed documentation for operational execution, ensuring that all processes are transparent, well-documented, and aligned with the company’s governance standards.

Qualifications

Bachelor’s degree in computer science, engineering, data science, statistics, mathematics, or a related field (Master’s degree preferred).
Minimum of 2 years of relevant experience in building, evaluating, scaling, and deploying machine learning pipelines, preferably within the Google Cloud Platform and Databricks ecosystem.
Strong programming skills in Python, with proficiency in data manipulation tools (SQL, Spark, Pandas) and machine learning frameworks (scikit-learn, TensorFlow, etc.).
Experience with CI/CD pipelines, Git version control, and data visualization tools to effectively communicate ML model behavior and business insights.
Expertise in AI/ML model design, frameworks, and libraries such as TensorFlow, PyTorch, scikit-learn, and more.
Solid understanding of Machine Learning fundamentals, with the ability to translate business requirements into effective ML solutions.
Excellent problem-solving skills, strong analytical abilities, and a sharp technical acumen.
Ability to communicate complex technical concepts in a clear, concise manner to both technical and non-technical stakeholders.
Strong team collaboration skills, with the ability to thrive in a fast-paced, dynamic environment.

Physical Requirements

Must be able to access all areas of the property and drive areas, with or without reasonable accommodation.
Ability to maintain composure under pressure, consistently meeting deadlines while interacting effectively with various stakeholders.
Must be able to work in a fast-paced environment, with exposure to noise, dust, and smoke.

Why Apply?

This role presents a fantastic opportunity for a Machine Learning Engineer who is eager to push the boundaries of technology and data science within a leading organization. If you are passionate about building cutting-edge ML solutions and have the expertise to drive business success through innovation, we encourage you to apply.

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