Job Description:
Machine Learning Engineer – Build Predictive Models
The Machine Learning Engineer plays a crucial role in designing, building, and deploying machine learning models and pipelines that drive AI-powered solutions for digital media and consulting projects. You will collaborate closely with data scientists and software engineers to transform experimental models into robust, scalable systems that operate efficiently in production environments.
In this role, you will take ownership of the entire machine learning lifecycle, starting with feature engineering to extract meaningful inputs from raw data. You’ll develop and refine algorithms that address complex business problems and improve predictive accuracy. Model training and rigorous performance tuning will be key responsibilities to ensure that solutions meet client expectations for speed, accuracy, and reliability.
Furthermore, you will be tasked with integrating machine learning models into client platforms and existing digital infrastructure. This includes developing APIs, creating deployment pipelines, and implementing monitoring tools to track model health and performance over time. Ensuring the scalability and maintainability of these systems is critical to delivering consistent, high-quality results.
You’ll also stay informed about the latest advancements in machine learning frameworks, tools, and cloud technologies. Experience with platforms such as TensorFlow, PyTorch, and cloud providers like AWS, GCP, or Azure will help you build efficient, cost-effective solutions.
Strong programming skills in languages like Python, Java, or Scala are essential. Your ability to write clean, modular code and document processes clearly will support collaboration across multidisciplinary teams. You’ll contribute to best practices in ML engineering, fostering innovation while ensuring operational excellence.
The Machine Learning Engineer is a key player in turning AI research into practical applications that enhance digital marketing, media optimization, and client outcomes. Your work directly influences the consultancy’s ability to deliver cutting-edge, data-driven solutions at scale.
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Responsibilities:
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Develop and implement machine learning models and algorithms.
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Collaborate with data scientists to operationalize models.
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Build data pipelines for training and inference.
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Optimize model performance and scalability.
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Deploy ML solutions on cloud platforms (AWS, GCP, Azure).
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Monitor and maintain models in production.
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Write clean, efficient, and well-documented code.
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Stay updated on emerging ML technologies and tools.
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Participate in code reviews and knowledge sharing.
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Troubleshoot and resolve ML system issues.
Preferred Qualifications:
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3+ years experience in machine learning engineering.
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Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
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Experience with cloud platforms and containerization (Docker, Kubernetes).
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Strong understanding of algorithms and data structures.
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Knowledge of data preprocessing and feature engineering.
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Experience with model deployment and monitoring.
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Bachelor’s or Master’s degree in computer science, AI, or related field.
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Strong analytical and problem-solving skills.
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Ability to work collaboratively in agile teams.
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Passion for applying ML to solve real-world problems.
