Senior Machine Learning Engineer - VTal Technology Solutions LLC
Cincinnati, OH 95131
About the Job
Seeking a Senior Machine Learning Engineer for a long term contract role with a leading US retail company. This is a hybrid position based in Cincinnati, OH.
Job Description
The Senior Machine Learning Engineer will lead the integration and operationalization of machine learning models. This role requires collaboration with data scientists and leadership teams, and a strong foundation in MLOps methodologies. Experience in diverse Client platforms, including Google Vertex AI and other cloud and open-source technologies, is essential. The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of the organization's Client infrastructure.
Qualifications
Job Description
The Senior Machine Learning Engineer will lead the integration and operationalization of machine learning models. This role requires collaboration with data scientists and leadership teams, and a strong foundation in MLOps methodologies. Experience in diverse Client platforms, including Google Vertex AI and other cloud and open-source technologies, is essential. The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of the organization's Client infrastructure.
Qualifications
- Minimum of 4 years of experience in MLOps, with a demonstrated ability to work with various Client platforms.
- Strong proficiency in Python and familiarity with data science methodologies.
- Experience with cloud technologies, particularly Google Cloud and Vertex AI, and adaptability to technologies like Microsoft Azure or open-source tools.
- Excellent communication skills, capable of bridging technical and business domains
- Experience in developing state-of-the-art techniques for multi-stage, personalized, context-aware, and sequential recommender systems.
- Hands-on experience working on recommender systems, drawing from Client techniques such as embedding based retrieval, reinforcement learning, transformers, and LLMs.
- Capable software engineering skills to lead a multi stage recommender system model lifecycle from inception to production.
Key Responsibilities
- Collaborate with data scientists to understand their needs and integrate their models into production systems efficiently.
- Act as a liaison between data science, MLOps, and leadership teams to facilitate communication and goal alignment.
- Develop, maintain, and manage scalable MLOps pipelines, particularly leveraging Google Vertex AI.
- Implement and manage Google Vertex AI's AutoML for high-quality machine learning models.
- Utilize Vertex AI Pipelines for streamlined operations and continuous modeling experiences.
- Maintain expertise in Client technologies and platforms, including TensorFlow, PyTorch, scikit-learn, and integrate them with Client frameworks.
- Work with various machine learning models such as vision, video, translation, and natural language processing.
- Efficiently manage, share, and reuse machine learning features at scale using Vertex AI Feature Store.
- Implement feature stores as a central repository for maintaining transparency in Client operations.
- Enable feature delivery with endpoint exposure while ensuring authority and security features are maintained.
- Assist with data labeling and management to ensure high-quality data for Client models.
- Collaborate with data engineers and data scientists to ensure the integrity and efficiency of data used in Client models.
- Ensure end-to-end integration for data to AI, including the use of BigTable/BigQuery for executing machine learning models on business intelligence tools.
- Monitor Client models in production, identify improvement opportunities, and implement optimizations.
- Stay updated with the latest trends in MLOps and Client technologies
Source : VTal Technology Solutions LLC