Machine Learning Engineer
1 month ago
Title: Machine Learning Engineer
Location: Bellevue, WA; Thousand Oaks, CA; San Diego, CA; South San Francisco, CA; Chicago, IL; Evanston, IL; Boston, MA; New York, NY; Princeton, NJ; Philadelphia, PA
Duration: FTE
The Challenge:
As a Machine Learning Engineer, you will be a key contributor to the client's AI Practice, building cutting-edge AI-powered data products and solutions. Your work will involve developing and deploying machine learning models, optimizing their performance, and ensuring their reliability in production environments.
Roles & Responsibilities:
• Design, develop, and deploy machine learning pipelines, including feature engineering, model training, and inference.
• Scale machine learning algorithms to handle massive datasets and meet stringent SLAs.
• Build and enhance ML engineering platforms and components.
• Implement robust ML Ops practices, including model monitoring, evaluation, and retraining.
• Write clean, efficient, and well-tested code.
• Collaborate effectively with cross-functional teams, including data scientists, engineers, and product managers.
• Stay up-to-date with the latest advancements in machine learning and AI.
Qualifications:
• Bachelor's or master’s degree in computer science, Statistics, or a related field.
• 2-4 years of experience in machine learning model development and deployment.
• Strong programming proficiency in Python and PySpark.
• Experience with ML platforms (e.g., Dataiku, SageMaker, MLflow).
• Expertise in cloud platforms (AWS, Azure, GCP) for model deployment.
• Solid understanding of machine learning algorithms and techniques.
• Proficiency in data structures, algorithms, and software design patterns.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
Preferred Qualifications:
• Experience with Spark or other distributed computing frameworks.
• Knowledge of DevOps, CI/CD, and data security.
• Experience with data engineering in big data systems.
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