Senior Machine Learning Engineer – ML/AI Team
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Job Description
Senior Machine Learning Engineer at A Place for Mom focused on developing ML and AI solutions. Designing and implementing advanced AI models to drive business impact using unstructured data.
Responsibilities:
- Study and transform data science prototypes using appropriate ML and GenAI architectures.
- Design and develop machine learning and LLM-powered systems using modern GenAI architectures (e.g., RAG, prompt engineering, embeddings, vector databases).
- Solve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks.
- Construct optimized data pipelines to feed both traditional ML models and LLM-based systems.
- Run machine learning tests and experiments and document findings and results.
- Implement and monitor model and data quality checks to ensure accuracy and consistency of our models and pipelines in production.
- Ensure system reliability, performance optimization, and responsible deployment of ML and LLM solutions in production.
- Manage the full model lifecycle, including retraining, performance monitoring, and continuous improvement.
- Partner with Product, Engineering and Business stakeholders to translate requirements into scalable AI/ML and GenAI solutions, contributing to system architecture and technical design.
- Provide technical guidance and support on AI/ML initiatives, delivering clear, actionable insights to stakeholders.
- Contribute to AI engineering standards and best practices across the organization.
- Create and maintain comprehensive documentation for ML and GenAI systems, including prompt libraries, evaluation frameworks, and architectural decisions.
- Establish and promote best practices across MLOps, LLMOps and AI system governance.
Requirements:
- Master’s degree in Computer Science, Mathematics, or a related field, or equivalent working experience
- 5+ years of proven experience as a Machine Learning Engineer, with significant experience working with data from structured and unstructured data sources, ETL processes, and data quality management.
- Strong proficiency in SQL, Databricks, AWS services, Python, and Spark.
- Experience with ML frameworks such as XGBoost, Scikit-learn, TensorFlow, Keras, or PyTorch.
- Hands-on experience building and deploying LLM-powered applications, including prompt engineering, evaluation frameworks, Retrieval-Augmented Generation (RAG), embedding models/vector databases.
- Familiarity with MLOps and/or LLMOps tooling and CI/CD workflows.
- Excellent analytical and problem-solving skills with a strong ability to derive insights from complex data sets.
- Effective communication skills with the ability to convey technical information and business impact to non-technical stakeholders.
Benefits:
- 401(k) plus match
- Dental insurance
- Health insurance
- Vision Insurance
- Paid Time Off
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