AI Engineer

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

📋 Description

• Construct and Maintain Production ML/AI Pipelines

• Design and uphold production ML and AI pipelines, encompassing training, evaluation, deployment, and monitoring.

• Develop data pipelines and prepare datasets for AI utilization.

• Create scalable architectures for model serving to facilitate real-time and batch inference.

• Ensure that AI and LLM systems are production-ready, stable, and high-performing.

• Apply MLOps Best Practices

• Implement tracking of experiments, model versioning, and reproducible training workflows.

• Establish procedures for the continuous evaluation and enhancement of machine learning and generative AI systems.

• Support the reliable lifecycle management of models from experimentation through to deployment and iteration.

• Monitor, Observe, and Enhance Models in Production

• Build and maintain monitoring systems to identify data drift, performance declines, and operational problems.

• Utilize evaluation frameworks and monitoring indicators to direct model enhancements over time.

• Assist teams in addressing production challenges with clear diagnostics and remediation strategies.

• Serve as a Trusted Technical Partner to Clients

• Collaborate directly with clients to elucidate AI concepts, trade-offs, and outcomes in straightforward, practical terms.

• Foster strong client relationships through thoughtful solutions and consistent delivery.

• Present technical methodologies and results to both technical and non-technical audiences.

• Collaborate Across Integrated Teams

• Work alongside data scientists and AI engineers to effectively operationalize models.

• Partner with software engineers to guarantee smooth deployment and integration into client platforms.

• Collaborate with analytics, strategy, and delivery teams to align MLOps solutions with client goals.

• Support Client-Facing Delivery

• Engage in client discussions by clarifying MLOps strategies, trade-offs, and outcomes in practical terms.

• Assist in translating client needs into operational AI solutions that are scalable and adaptable.

• Ensure consistent, high-quality delivery across various client engagements.

⛳️ Requirements

• Bachelor’s degree in a relevant discipline or equivalent practical experience; Master’s degree is preferred.

• 2+ years in a technical position focused on machine learning, data platforms, or AI systems (2+ years post-Master’s if applicable).

• Practical experience in deploying and managing machine learning or generative AI models in production settings.

• Strong knowledge of MLOps practices, including experiment tracking, model versioning, and monitoring.

• Experience in building data and model pipelines within distributed environments.

• Familiarity with model evaluation frameworks and performance monitoring methods.

• Exposure to large language models and applied AI use cases.

• Strong skills in object-oriented programming.

• Working knowledge of Databricks.

• Proficiency in Python, SQL, and related analytics or engineering tools; familiarity with BI tools such as Tableau, Power BI, or Domo is a plus.

• Experience in owning or leading technical workstreams within collaborative settings.

• Excellent communication skills, including the ability to convey technical concepts to non-technical stakeholders.

• Experience in integrated marketing, digital agency, marketing services, or consulting environments is preferred.

🏝️ Benefits

• Medical, dental, and vision coverage

• 401(k) retirement plan

• Paid holidays

• Flexible Time Off (FTO)

• Additional programs focused on wellness, financial security, and professional growth