AI / ML Engineer

Technology:
Python, GCP, Docker, AWS, TypeScript, Azure

Role:

• Evaluate, develop, and support a variety of machine learning model types, along with various NLP data pipelines to co-create new AI products.
• Apply state-of-the-art GenAI/ML/NLP and full-stack software engineering techniques to develop end-to-end intelligent solutions for unique business problems.
• Set up fine-tuning and evaluation pipelines on AWS, GCP, and other compute providers.
• Manage AI workload compute resources and monitor experiments, keeping track of results.
• Design, build, and maintain highly scalable, cloud-based services using TypeScript, Python, and React.
• Provide hands-on technical guidance and leadership throughout the lifecycle of GenAI/NLP-based projects.
• Create tooling to support the ML model lifecycle, including model evaluations, dataset curation, and training infrastructure.
• Build scalable infrastructure for LLM model orchestration with a focus on an intuitive user experience.
• Make architecture and technology decisions that balance business needs, innovation, security, and reliability.
• Enhance platform performance and scalability, focusing on creating seamless user experiences.
• Collaborate with cross-functional teams to deliver AI-powered products.

Qualifications:

• Degree in Data Science, Computer Science, Informatics, Life Sciences, Physics, Applied Mathematics, Statistics, or a related field.
• Proficiency in leveraging cloud-based machine learning resources such as AWS or Google Cloud for model training and productization.
• Strong understanding of Software Engineering and Agile Software Development Life Cycle principles.
• Expertise in Python, with good proficiency in SQL, Scala, or Java.

Responsibilities:

• Work with large datasets, build and evaluate models, and integrate them with other systems.
• Strong understanding of machine learning algorithms, model deployment, and monitoring.
• 2-5 years of experience as a Data Scientist, Machine Learning Engineer, or NLP Engineer.
• 2-5 years of experience working with structured, semi-structured, and unstructured datasets.
• Deep hands-on experience with LLMs and GenAI concepts (e.g., prompt engineering, RAG, GraphRAG, fine-tuning).
• Proficiency in cloud-based machine learning resources for model training and productization (AWS, GCP).
• Expertise in Python, with proficiency in SQL, Scala, or Java.
• Ability to work in a fast-paced environment, managing multiple projects and effectively communicating with diverse teams.
• Model Development: Design, develop, and implement machine learning models to solve business challenges.
• Model Evaluation and Optimization: Evaluate model performance, fine-tune parameters, and optimize models for accuracy and efficiency.
• AI/ML Deployment: Develop and deploy AI/ML models using AWS AI/ML services (e.g., SageMaker, Rekognition, Comprehend) and collaborate with data scientists and engineers.
• Containerization: Design, implement, and manage containerized applications using AWS Cloud Containerization services (e.g., ECS, EKS) and Docker, developing CI/CD pipelines for automated deployment and scaling.

Presentation Skills:

• Ability to develop visually simple and appealing PowerPoint presentations.
• Comfort with articulating and communicating key messages to a broad range of stakeholders.