AI/ML Lead Engineer

Title: AI/ML Lead Engineer

Location: Remote

FTE only.

Must have Banking domain experience

Key Responsibilities:

· Full ML Lifecycle Management: Drive projects from initial ideation to production deployment, including data pipeline development, model training, validation, and serving.

· LLM & Agentic Development: Design, implement, and optimize solutions utilizing Large Language Models (LLMs) and developing sophisticated Agentic AI systems to solve complex business problems.

· Platform Expertise: Leverage and integrate core generative AI platforms, including Gemini and Amazon Bedrock, to build scalable and efficient solutions.

· MLOps & Tools: Implement MLOps best practices, utilizing tools like MLFlow for experiment tracking, model versioning, and pipeline orchestration.

· Quality Assurance: Develop and execute comprehensive testing strategies for LLM applications, including utilizing frameworks like DeepEval for prompt engineering and model output quality.

· Analytical Skill: Apply strong analytical skills to evaluate model performance, diagnose issues, and iterate on solutions to achieve maximum business impact.

· Collaboration: Work closely with cross-functional teams (data scientists, product managers, and software engineers) to define requirements and deliver integrated AI features.

Required Qualifications:

· Experience: 8+ years of professional experience in Machine Learning Engineering, AI Development, or a closely related field.

· Technical Proficiency:

· Expertise in Python and core ML/Data Science libraries (e.g., PyTorch, TensorFlow, Scikit-learn).

· Proven experience in deploying models on major cloud platforms (GCP, AWS, or Azure).

· Deep understanding of the architecture and fine-tuning of Large Language Models.

· Domain Knowledge: Practical experience with MLOps tools (e.g., MLFlow) and validation frameworks (e.g., DeepEval).

· Problem Solving: Demonstrated ability to apply analytical skills to complex, ambiguous problems and translate insights into actionable engineering solutions.

Preferred Qualifications:

· Hands-on experience developing applications or services using Google's Gemini API or models.

· Direct experience with AWS services related to AI/ML, particularly Amazon Bedrock.

· Experience in building and managing multi-step, reasoning-based Agentic AI systems.

· Prior experience in optimizing models for latency and cost efficiency in a production environment.