Senior Engineer – ML Operations

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

📋 Description

• Take ownership of the complete ML and LLM lifecycle, including deployment.

• Oversee experiment tracking, model and prompt registries, version control, lineage, and reproducibility.

• Design and manage batch and low-latency model-serving infrastructure, which encompasses LLM inference.

• Enhance autoscaling, GPU efficiency, batching, quantization, caching, and overall performance.

• Turn agentic workflows and automations into scalable, repeatable, and reliable services.

• Implement containerized and sandboxed execution with secure integration of tools and data.

• Establish CI/CD processes, testing protocols, offline and online evaluations, guardrails, and safe deployment strategies.

• Monitor the quality of models and agents, including drift, latency, token usage, and associated costs.

• Set up tracing, automated alert systems, and feedback mechanisms.

• Manage GPU and accelerated-compute scheduling, quota and utilization oversight, provider routing, rate limits, and CUDA image hygiene.

• Develop self-service ML and agent tools, golden paths, and reusable templates.

• Define MLOps and LLMOps standards and best practices.

• Collaborate with Danaher operating companies, platform teams, data scientists, engineers, and business teams.

• Offer technical leadership while actively engaging in architecture and delivery.

• Report directly to the Senior Director of Data and AI Platform.

⛳️ Requirements

• A degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience.

• Over 4 years of experience in software, ML, or infrastructure engineering.

• Practical hands-on experience in MLOps/LLMOps.

• Proven record of deploying ML models or AI agents at scale.

• Extensive experience with ML and LLM lifecycle tools, including experiment tracking, evaluation, observability/monitoring, model registry, versioning, lineage, and reproducibility.

• Strong proficiency with Docker and Kubernetes, particularly in scaling GPU and inference workloads.

• Experience with a major cloud platform; Azure is preferred.

• Familiarity with Azure ML or Azure AI Foundry.

• Experience utilizing IaC and CI/CD for ML applications.

• Proficient in Python and knowledgeable in Bash.

• Willingness to travel up to 10%.

• Capability to work remotely from home within the USA.

🏝️ Benefits

• Comprehensive benefits package.

• Paid time off.

• Medical insurance.

• Dental insurance.

• Vision insurance.

• 401(k) plan.

• Bonus/incentive pay.

• Flexible remote working arrangement.

• Opportunity to work from home.

• Reasonable accommodations for applicants and employees with disabilities.