Overview
On Site
$60 - $65
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 12 Month(s)
Skills
Machine Learning
Gen ai
Job Details
Role- Machine Learning Engineer
Location - Malvern,PA Oniste role .(Local profiles only with local ID proof)
Duration -- 12 months extendable
Onsite interview
Role #1
Description
We are seeking an experienced Machine Learning Engineer to join our AI/ML Engineering team.
- You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines, and building scalable AI/ML solutions, including large language models (LLMs).
- The ideal candidate will possess a robust background in traditional machine learning, deep learning, and significant experience with large datasets and cloud-based AI services.
Responsibilities
- Develop and optimize complex data pipelines, applying machine learning engineering principles to enhance efficiency and scalability.
- Integrate and optimize data and model pipelines within production environments, diagnosing data inconsistencies and documenting assumptions.
- Collaborate with data science teams to review model-ready datasets and feature documentation, ensuring completeness and accuracy.
- Perform data discovery and analysis of raw data sources, applying business context to meet model development needs.
- Comfort with exploratory data exploration and tracking data lineage during inception or root cause analysis.
- Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts.
Qualifications
- Around 5-8 years of relevant work experience.
- At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).
- Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.
- Strong understanding of cloud technologies, including AWS and Azure.
- Experience with API design and development is a plus.
- Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
- Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.
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