AI/ML Engineer

Key Responsibilities

• Collaborate with business teams to understand requirements and translate them into ML models and prompt-based solutions.

• Design, develop, and fine-tune machine learning models, particularly those involving LLMs and generative AI.

• Optimize and adapt prompt engineering strategies to improve model performance and relevance.

• Integrate and deploy models using AWS services including Bedrock, S3, ECS, EC2, Lambda and other AI/ML related services.

• Build and maintain scalable data pipelines and APIs to support ML workflows.

• Monitor model performance and iterate based on feedback and metrics.

• Stay current with advancements in AI/ML and cloud technologies to ensure our solutions remain cutting-edge.

Required Qualifications

• Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field.

• 3+ years of experience in machine learning, data science, or AI engineering.

• Hands-on experience with LLMs (e.g., OpenAI, Anthropic, Cohere) and prompt engineering.

• Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).

• Deep experience with AWS services, especially Bedrock, S3, EC2, and Lambda

• Familiarity with MLOps practices and tools for model deployment and monitoring.

• Excellent problem-solving skills and ability to communicate technical concepts to non-technical stakeholders.

• Strong programming skills in data analytics related languages and libraries, such as Python, R, Pandas, or JavaScript.

• Experience with AWS SageMaker for model development and model deployment.

• Understanding of quantitative/statistical/ML/AI modeling methodologies.

• Experience in ML engineering, including hands-on experience with Generative AI/LLMs.

• Experience with developing and deploying AI Agents for business problems.

Preferred Qualifications

• Experience with fine-tuning or customizing foundation models.

• Knowledge of data privacy and security best practices in cloud environments.

• Familiarity with containerization (Docker) and container orchestration is a plus.