Danaher Corporation Logo

Danaher Corporation

Senior Engineer - ML Operations

Posted 2 Days Ago
Remote
Hiring Remotely in USA
180K-220K Annually
Senior level
Remote
Hiring Remotely in USA
180K-220K Annually
Senior level
Own the end-to-end machine learning and LLM lifecycle, taking models and agentic AI workflows from experimentation into reliable, scalable production. Design MLOps infrastructure, serving, orchestration, CI/CD, evaluation, observability, and GPU optimization. Build self-service tooling and establish LLMOps standards while partnering with engineering and business teams. The role is fully remote and involves up to 10% travel.
The summary above was generated by AI

Bring more to life.


At Danaher, our work saves lives. And each of us plays a part. Fueled by our culture of continuous improvement, we turn ideas into impact – innovating at the speed of life.


Our 60,000+ associates work across the globe at more than 15 unique businesses within life sciences, diagnostics, and biotechnology.


Are you ready to accelerate your potential and make a real difference? At Danaher, you can build an incredible career at a leading science and technology company, where we’re committed to hiring and developing from within. You’ll thrive in a culture of belonging where you and your unique viewpoint matter.


Learn about the Danaher Business System which makes everything possible.

The Senior MLOps Engineer is responsible for owning significant parts of the machine learning and agentic AI lifecycle that powers Danaher’s next generation of AI-driven products and automations. You will take models and AI agents from experimentation to reliable, scalable production. In this high-impact role, you will design and operate the pipelines, serving infrastructure, orchestration, and observability that let data scientists, engineers, and business teams build and run ML models and agentic workflows with speed, reproducibility, and rigor. You will partner with teams across Danaher’s operating companies to turn promising AI prototypes into governed, production-grade agentic automations that run efficiently at scale on shared compute.


This position reports to the Senior Director, Data and AI Platform and is part of the Chief Information Officer (CIO) Office located in Washington, DC and will be fully remote.


In this role, you will have the opportunity to:

  • Own the end-to-end ML and LLM lifecycle and deployment: experiment tracking, model and prompt registries, versioning, lineage, and reproducibility (e.g., MLflow, Weights & Biases); design and operate model serving for batch and low-latency online inference, including LLM inference, with autoscaling, GPU efficiency, and performance optimization (batching, quantization, caching).
  • Partner with engineering and business teams to productionize agentic workflows and automations: turn agent prototypes into scalable, repeatable, reliable services using orchestration frameworks (e.g., LangGraph, Claude Agent SDK, Airflow, Prefect, etc) with containerized, sandboxed execution, secure tool and data integrations (e.g., MCP), and support for many concurrent users and workflows without contention.
  • Implement CI/CD, evaluation, and observability for ML and agents: automate the path from code to validated production through testing, offline and online evaluations, guardrails, and safe deployment patterns (blue/green, canary); monitor model and agent quality, drift, latency, token usage, and cost; implement tracing, automated alerting, and feedback loops using observability tools (e.g., OpenTelemetry).
  • Drive compute and cost efficiency for AI workloads: GPU and accelerated-compute scheduling, quota and utilization management, LLM provider/gateway routing and rate limits, and driver/CUDA image hygiene, partnering with the platform team to maximize value from contended, high-demand resources.
  • Build self-service ML and agent tooling and provide technical leadership: develop golden paths and reusable templates that let teams build, evaluate, deploy, and monitor models and agents without deep infrastructure expertise, treating AI enablement as a product; set MLOps and LLMOps standards and best practices while staying hands-on with architecture and delivery.

The essential requirements of the job include:

  • Degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 4+ years of software, ML, or infrastructure engineering experience, including hands-on MLOps/LLMOps and a track record of taking ML models or AI agents into production at scale.
  • Strong experience with ML and LLM lifecycle tooling: experiment tracking, evaluation, observability/monitoring, model registry, versioning, lineage, and reproducibility (e.g., MLflow, Weights & Biases, Langfuse).
  • Strong experience with containerization and orchestration (Docker, Kubernetes), including scaling GPU and inference workloads, and with a major cloud platform (Azure preferred) and its AI services (e.g., Azure ML, Azure AI Foundry), using IaC and CI/CD for ML.
  • Proficiency in Python (and familiarity with Bash) for automation, tooling, and pipeline development.

Travel, Motor Vehicle Record & Physical/Environment Requirements: 

  • Ability to travel – up to 10%

It would be a plus if you also possess previous experience in:

  • Building and operating agentic systems in production, including multi-agent orchestration, tool calling, retrieval-augmented generation (RAG), and agent security practices such as sandboxing, permission setting, and prompt-injection defenses.
  • Operating ML or AI systems in a regulated environment (GxP, SOX, or HIPAA), including model traceability, audit evidence, and AI governance controls.
  • High-performance LLM serving and AI gateway platforms (e.g., vLLM, TGI, Triton, LiteLLM) or serverless GPU compute platforms.

Danaher offers a broad array of comprehensive, competitive benefit programs that add value to our lives. Whether it’s a health care program or paid time off, our programs contribute to life beyond the job. Check out our benefits at Danaher Benefits Info.


At Danaher, we believe in designing a better, more sustainable workforce. We recognize the benefits of flexible, remote working arrangements for eligible roles and are committed to providing enriching careers, no matter the work arrangement. This position is eligible for a remote work arrangement in which you can work remotely from your home. Additional information about this remote work arrangement will be provided by your interview team. Explore the flexibility and challenge that working for Danaher can provide.


The annual salary range for this role is $180K-$220K. This is the range that we in good faith believe is the range of possible compensation for this role at the time of this posting. This range may be modified in the future. 

This job is also eligible for bonus/incentive pay.

We offer comprehensive package of benefits including paid time off, medical/dental/vision insurance and 401(k) to eligible employees. 

  

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.

#LI-Remote

Join our winning team today. Together, we’ll accelerate the real-life impact of tomorrow’s science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life.


For more information, visit www.danaher.com.


Danaher Corporation and all Danaher Companies are committed to equal opportunity regardless of race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity, or other characteristics protected by law.


The U.S. EEO posters are available here.


For candidates who are based outside of New York City or who are applying for roles outside of New York City, for more information about conditions of any job offer please click here


We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact:1-202-419-7762 or [email protected].

Similar Jobs

3 Days Ago
Remote or Hybrid
165K-250K Annually
Senior level
165K-250K Annually
Senior level
Cloud • Digital Media • News + Entertainment • On-Demand
Build and operate Philo’s ML and LLM infrastructure, including AWS and Kubernetes platforms, GPU scheduling, model serving, inference optimization, monitoring, evaluation, experimentation, and CI/CD. The role establishes infrastructure best practices, reliability, security, scalability, and Infrastructure as Code while supporting recommendation, video classification, and agent workloads. It also involves collaborating with engineers and vendors to deploy, instrument, and manage production systems.
Top Skills: AirflowAlbAmazon BedrockAnthropicAWSC++CloudFormationCloudwatchDagsterDatadogDnsDockerDvcElasticacheElbElkFeastFluentdGitlabGoGrafanaHTTPIamInfluxdbJavaScriptJenkinsKubeflowKubernetesLakefsLinuxLitellmMetaflowMlflowNlbNvidia TritonOpenaiPgvectorPineconePrometheusPythonRagRayRdsRoute 53RubySqsTcp/IpTectonTensorrt-LlmTerraformTgiTickTypescriptVllmVpcWeaviateWeights & Biases
Yesterday
In-Office or Remote
184K-357K Annually
Senior level
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
Develop and deploy AI infrastructure solutions across NVIDIA cloud, partner, and hyperscale environments. Build distributed training, inference, and MLOps pipelines; manage Kubernetes-based GPU workloads; optimize performance, cost, and reliability; and implement observability and SLO/SLA monitoring. Provide hands-on technical support to strategic customers and partners, troubleshoot production issues, integrate enterprise systems, and create implementation guides, runbooks, and postmortems.
Top Skills: AnsibleApi IntegrationsCi/CdContainersCudaDistributed ComputingDockerGitopsGoGpu SchedulingGrafanaInfinibandKubernetesLinuxMlopsNemoNimNvidia Dgx CloudNvidia NcpNvidia Neo CloudObservabilityOpentelemetryPrometheusPythonPyTorchRoceSlo/Sla MonitoringTensorFlowTerraformTriton
5 Days Ago
In-Office or Remote
191K-261K Annually
Senior level
191K-261K Annually
Senior level
Information Technology
Build and operate production machine-learning systems, including training, deployment, monitoring, retraining, APIs, data pipelines, dashboards, and orchestration. Develop customer-facing workflows for model refreshes and health visibility, automate validation and rollout processes, and improve Kubernetes, CI/CD, observability, and deployment tooling. Partner with customers and internal teams to turn tailored solutions into reusable platform capabilities while ensuring reliability, rollback safety, and operational maintainability.
Top Skills: AirflowAPIsAWSCi/CdData PipelinesFastapiFeature PipelinesHiveKubernetesMlflowModel RegistriesObservabilityPythonS3SparkSQLWorkflow Orchestration

What you need to know about the Austin Tech Scene

Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.

Key Facts About Austin Tech

  • Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
  • Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
  • Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
  • Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account