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As an MLOps Engineer, you will play a pivotal role in developing and deploying advanced AI solutions that drive our client's mission forward. This role centers on building and implementing models using Machine Learning (ML), Natural Language Processing (NLP), Generative AI (GenAI), and Large Language Models (LLMs). You'll collaborate closely with data scientists, ML engineers, and product teams to translate business objectives into scalable, production-ready AI systems.

Key Responsibilities

• Deliver AI solutions aligned with the enterprise AI strategy.
• Design and implement custom ML, GenAI, NLP, and LLM models for both batch and streaming pipelines.
• Build components for data ingestion, preprocessing, search/retrieval, and Retrieval-Augmented Generation (RAG).
• Collaborate with data science and software engineering teams to integrate AI models into production systems.
• Stay current with emerging AI/ML trends and recommend innovative applications.
• Ensure adherence to best practices in data privacy, security, and bias mitigation.
• Demonstrate and promote company values: accountability, innovation, integrity, quality, and teamwork.
• Maintain consistent, reliable attendance and foster inclusive behaviors.

Minimum Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field; or HS Diploma/GED plus 4+ years of relevant experience in lieu of a degree.
• 3+ years of professional experience in AI/ML model development.
• Hands-on experience with machine learning frameworks, Python, and cloud platforms (AWS, Azure, or GCP).
• Proven ability to quickly learn new technologies and apply AI/ML techniques to solve business problems.
• Strong analytical and problem-solving skills.
• Awareness of ethical considerations in AI systems.

Preferred Qualifications

• Experience deploying Generative AI solutions at scale.
• Familiarity with fine-tuning LLMs/SLMs and working with teacher-student frameworks or model distillation.
• Understanding of human-in-the-loop model alignment techniques.
• Exposure to agentic frameworks and deploying agent-based AI solutions.

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