Overview
Skills
Job Details
Job Title: Data Scientist/ML Engineer
Location: Seattle, WA (Hybrid-Onsite)
Employment Type: Contract(C2C/W2)
Minimum Experience Required - 10 Years
Job Summary:
We are seeking a talented and results-driven Machine Learning Engineer to join our team. The ideal candidate will have hands-on experience in developing, deploying, and optimizing machine learning models and AI solutions. You will work on cutting-edge projects involving Natural Language Processing (NLP), Deep Learning, and AI prompt-response systems while ensuring scalable data pipelines and system performance.
Key Responsibilities:
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Design, develop, and deploy machine learning models for real-world business applications.
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Apply natural language processing (NLP) techniques to extract insights from unstructured text data.
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Develop and maintain AI prompt-response systems for generative AI use cases.
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Work with deep learning frameworks (e.g., TensorFlow, PyTorch) to build and fine-tune neural network models.
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Perform data modeling, preprocessing, and feature engineering for large datasets.
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Write clean, modular, and scalable Python and Java code to support ML workflows.
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Use MySQL and other data storage solutions for data querying and management.
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Perform static code analysis and ensure code quality and maintainability.
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Deploy and monitor ML models on AWS cloud infrastructure.
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Collaborate with cross-functional teams including Data Scientists, Backend Engineers, and Product Managers.
Required Skills & Qualifications:
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Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related field.
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Proven experience with machine learning, deep learning, and NLP techniques.
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Strong proficiency in Python; experience with Java is a plus.
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Solid understanding of data modeling and relational databases (MySQL).
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Experience with AWS services such as S3, SageMaker, Lambda, or ECX.
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Familiarity with static code analysis tools (e.g., SonarQube).
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Ability to design AI prompt-response systems for generative AI platforms.
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Excellent problem-solving and communication skills.
Preferred Qualifications:
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Experience with LLMs and prompt engineering.
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Familiarity with MLOps tools and practices.
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Understanding of REST APIs and deployment pipelines.