
AI/ML Solutions Architect
16 hours ago
We are seeking an experienced Senior 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).
Job Description:You will play a key role in driving the development of innovative AI/ML solutions that meet business needs. Your primary responsibility will be to design, develop, and deploy machine learning models that drive business value.
- 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.
- Employ experimental methodologies, statistics, and machine learning concepts to create self-running AI systems for predictive modeling.
- 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.
- Engage with internal stakeholders to understand business processes and translate requirements into analytical approaches.
- Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts.
- Serve as a domain expert in machine learning engineering on cross-functional teams for significant initiatives.
- Stay updated with the latest advancements in AI/ML and apply them to real-world challenges.
Candidates must have a strong understanding of machine learning engineering principles, experience with large-scale data processing, and proficiency in programming languages such as Python.
Requirements:- Undergraduate degree or equivalent experience; a graduate degree is preferred.
- Minimum of 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, and experience with NoSQL databases.
- Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.
- Experience with API design and development is a plus. Docker Kubernetes
- Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
- Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols.
- Understanding of solution architecture for building end-to-end machine learning data pipelines.
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