Machine Learning Engineer

1 month ago


New York, United States PERMEVO Full time

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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