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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