Machine Learning Engineer

About the role

Beacon Hill Technologies seeks a highly technical engineer to oversee end-to-end platform integration and orchestration within their clients' AI/ML ecosystems. The focus is on system interoperability, tool connectivity, workflow management, and system performance monitoring.

Responsibilities

• Connect systems and tools, ensuring traceability and workflow orchestration
• Implement observability across model, data, and infrastructure pipelines
• Ensure seamless integration between platforms and enforce structured delivery workflows
• Enable deep visibility into system performance and usage

Requirements

• 3+ years of MLOps or ML platform engineering experience
• Strong experience with cloud platforms, especially Microsoft Azure
• Hands-on experience integrating enterprise systems, such as ServiceNow
• Experience with data platforms, particularly Snowflake
• Proficiency in CI/CD pipelines (e.g., Azure DevOps, GitHub)
• Experience implementing observability using tools like Datadog
• Strong understanding of API integrations and distributed systems
• Expertise in telemetry (logs, metrics, traces), workflow automation, and orchestration
• Familiarity with DevOps practices and release management
• Ability to work across multiple teams and quickly understand existing systems

Nice to Have

• Experience with LLM/AI systems observability, including usage tracking and model metrics
• Familiarity with Snowflake Cortex or similar AI/data platform capabilities
• Experience designing end-to-end traceability frameworks
• Knowledge of data pipeline architecture and data lineage
• Experience aligning tagging strategies and identifier schemas across systems
• Strong collaboration skills in cross-functional environments