Senior Machine Learning Engineer – Generative AI

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, integrate, optimize, and sustain AI-driven applications utilizing generative models.

• Assist throughout the entire product lifecycle of generative AI offerings.

• Collaborate with UX designers, engineering teams, product management, business stakeholders, infrastructure personnel, development teams, and support teams.

• Create and implement applications leveraging large language models and other generative models.

• Conduct prompt engineering, model integration, development of Retrieval-Augmented Generation (RAG) pipelines, and scalable AI service creation.

• Assess, test, monitor, and enhance AI systems in a production environment.

• Utilize domain data to refine prompts and enhance AI workflows.

• Generate documentation and enablement resources for generative AI solutions.

• Operate independently with minimal oversight while engaging with cross-functional teams.

• Review code and prompt implementations, offering insights based on engineering and responsible AI best practices.

• Document, evaluate, and ensure adherence to quality and change control standards.

• Guarantee that user stories are developer-ready, clear, and testable.

• Write custom code or scripts to automate infrastructure, monitoring services, and testing scenarios.

• Conduct destructive testing to validate production resilience.

• Configure commercial off-the-shelf solutions to meet changing business requirements.

• Develop dashboards, logging, alerting, and proactive issue resolution strategies.

• Address inquiries from product and support teams.

• Provide application support for software operating in a production setting.

• Oversee production Service Level Objectives.

• Review performance and capacity regarding code, infrastructure, data, message processing, and prediction quality.

• Report to a Software Engineering Manager or Senior Software Engineering Manager.

• Maintain no direct reports.

⛳️ Requirements

• Must be at least eighteen years of age.

• Must be legally authorized to work in the United States.

• Minimum educational requirement: high school diploma and/or GED.

• At least 2 years of professional experience.

• Proficient in Python and contemporary AI development frameworks.

• Experience in creating Generative AI applications utilizing large language models (LLMs).

• Familiarity with prompt engineering, optimization, and evaluation methodologies.

• Experience integrating AI models via APIs from platforms such as Google, OpenAI, or Anthropic.

• Knowledge of GenAI frameworks, such as the Google Agent Development Kit (ADK).

• Experience in implementing Retrieval-Augmented Generation (RAG) pipelines using vector databases.

• Proficient in working with vector databases such as Google Vertex AI Search.

• Experience in developing conversational AI systems or AI assistants.

• Knowledge of responsible AI practices, including bias mitigation and safety measures.

• Familiarity with graph databases, knowledge ingestion pipelines, and data mesh architectures.

• Experience in implementing CI/CD pipelines, monitoring, and automated workflows for dependable AI model deployment and lifecycle management.

• Knowledge in monitoring, assessment, and optimization of production AI systems.

• Experience with Google Cloud Platform and AI/ML components, such as Vertex AI and BigQueryML.

• Familiarity with data engineering practices and large-scale data platforms like BigQuery and Data Store.

• Proficient in a modern scripting language, preferably Python.

• Experience with GPU acceleration technologies such as CUDA and cuDNN.

• Familiarity with front-end technologies and frameworks including Node.js, HTML, CSS, JavaScript, ReactJS, and D3.

• Experience writing SQL queries for relational databases.

• Understanding of production systems design, including High Availability, Disaster Recovery, Performance, Efficiency, and Security.

• Familiarity with cloud computing platforms, automation strategies, and machine learning services.

• Knowledge of defensive coding practices and patterns for high availability.

• Familiarity with A/B testing and REST design for scalable web service architecture.

• Understanding of advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and the generation and utilization of embeddings.

🏝️ Benefits

• Remote/Virtual work arrangement.

• Overnight travel typically required only 5% to 20% of the time.