We are seeking a highly skilled Machine Learning Engineer with deep expertise in Generative AI to design, deploy, and manage LLM-powered applications in production. This role requires strong hands-on experience building, training, and launching models, with a focus on prompt engineering and optimizing real-world application performance.

Key Responsibilities:

Design, develop, and deploy LLM-based applications leveraging platforms such as Gemini and/or GPT.
Build, train, fine-tune, and optimize models for production environments.
Apply effective prompt engineering techniques to improve model performance and outputs.
Work closely with business stakeholders and subject matter experts to understand use cases and integrate AI solutions into existing applications.
Manage cloud-based AI infrastructure, ensuring scalability, reliability, and cost-efficiency.
Collaborate with cross-functional engineering and analytics teams to integrate AI capabilities into enterprise applications.

Required Qualifications:

3+ years of experience as a Machine Learning Engineer, Data Scientist, or similar role.
Proven hands-on experience with Generative AI models and platforms (Gemini and/or GPT strongly preferred).
Strong proficiency in Python and experience with data preprocessing, feature engineering, and model evaluation.
Expertise with Google Cloud Platform (GCP), particularly Vertex AI for model training, deployment, and monitoring.
Experience building and deploying LLM-powered applications in production environments.
Strong understanding of prompt engineering techniques and best practices.

Preferred Qualifications:

Background in both Data Science (60%) and Machine Learning Engineering (40%), with proven ability to push code to production.
Experience working with RDBMS & NoSQL databases (e.g., PostgreSQL, MongoDB, BigQuery).
Prior experience in high-volume, business-critical application environments.
Healthcare domain experience (nice to have, but not required).

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Generative AI / Machine Learning Engineer

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