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Description:
This is a CONTRACT TO HIRE OPPORTUNITY; the ideal candidate should be able to start on 10/1/2024.
The Lead MLOps Engineer will be instrumental in architecting data solutions, designing and optimizing data pipelines, and operationalizing machine learning models.
This position requires a strong technical foundation, strategic thinking, and the ability to collaborate across disciplines to drive innovation and data-driven excellence.
The role involves creating high-quality backend architectures that leverage cloud technologies, blending business acumen, performance optimization, cost-efficiency, and practical implementation.
Core responsibilities include sustaining and deploying AI models aligned with organizational standards and ethical guidelines, developing various GenAI tools to translate natural language inputs into coherent content, and enhancing tool output through AI agents.
The engineer will build and maintain various API feeds, assure the integrity of data, oversee model management, and chronicle the lineage of generative AI deployments.
The role requires staying updated on the generative AI landscape’s evolution and infusing the AI toolkit with compliant solutions.
The engineer will engage in the perpetual refinement of the technology stack, fostering a culture of innovation and experimentation.
Requirements:
A robust analytical foundation in machine learning, data science, and model optimization is required.
Proficiency in large language models and their utility in synthesizing unprecedented data forms is essential.
Competence in manipulating heterogeneous datasets and enhancing them when required is necessary.
Exceptional collaborative and communicative abilities to synergize effectively with diverse teams are a must.
Experience delivering gen-ai driven solutions is required.
Strong applied machine learning and natural language processing knowledge with experience working at an asset manager is essential.
Practical experience with cloud platforms and crafting enterprise-grade solutions leveraging generative AI models is necessary.
Practical experience working with various document processing libraries in Python is required.
Insight into the frameworks governing AI, including security, privacy, compliance, and scalability, is essential.
A dynamic and agile mindset, coupled with a user-centric philosophy towards technological advancement, is required.
Benefits:
Employees can work remotely, providing flexibility in work arrangements.
The opportunity to work with an award-winning company focused on advanced analytics, data, and technology.
The role offers a chance to lead innovative projects and contribute to the evolution of generative AI solutions.
The position allows for professional growth and development in a rapidly evolving field.
The company fosters a culture of innovation and experimentation, encouraging continuous learning and improvement.