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Own the end-to-end machine learning lifecycle, taking models from experimentation to scalable production for AI-driven research. Design and operate pipelines, serving infrastructure, and observability tools to support large-scale protein design and structure prediction workloads.
Requires a degree in Computer Science, Engineering, or a related field with 5+ years of software or ML infrastructure experience. Must have a proven track record of productionizing ML models at scale using containerization and cloud platforms.
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 Staff Engineer - ML Operations is responsible for owning significant parts of the machine learning lifecycle that powers Danaher's next-generation AI-driven research. You will be taking models from experimentation to reliable, scalable production. In this highly impactful role, you will design and operate the pipelines, serving infrastructure, and observability that let our scientists run large-scale ML experiments with speed, reproducibility, and rigor. You will work hand in hand with bioinformatics and computational biology teams running cutting-edge protein design and structure prediction workloads, ensuring those workloads run efficiently at scale on shared accelerated compute.
This position reports to the Senior Director, Data and AI Platform and is part of the Chief Scientific Officer (CSO) Office and will be fully remote.
In this role, you will have the opportunity to:
Own the end-to-end ML lifecycle and deployment — experiment tracking, model registry, versioning, lineage, and reproducibility (e.g., MLflow, Weights & Biases, Kubeflow); design and operate model serving for batch and low-latency online inference with autoscaling, GPU efficiency, and performance optimization (batching, quantization, caching) — so every model in production is traceable, auditable, and performant.
Partner with bioinformatics and computational biology teams to productionize large-scale protein design and structure-prediction experiments turning research workflows into scalable, repeatable, high-throughput pipelines (Airflow, Dagster, Prefect, Nextflow) with containerized, reproducible execution that serve many concurrent researchers without contention.
Implement CI/CD, continuous training, and observability for ML — automate the path from model code to validated production through testing, evaluation gates, and safe deployment patterns (blue/green, canary); monitor model performance, data/prediction drift, latency, and cost; implement automated retraining and alerting instrumented via OpenTelemetry/Prometheus/Grafana so issues are caught before they reach users.
Drive GPU and accelerated-compute efficiency — scheduling, quota and utilization management, and driver/CUDA image hygiene — partnering with the platform team to maximize value from contended, high-demand compute.
Build self-service ML tooling and provide technical leadership — develop golden paths that let data scientists and researchers train, track, serve, and monitor models without deep infrastructure expertise, treating ML enablement as a product; set MLOps standards and best practices while staying hands-on with architecture and delivery.
The essential requirements of the job include:
Degree in Computer Science, Engineering, Computational Biology, or a related technical field, or equivalent practical experience.
5+ years of software, ML, or infrastructure engineering experience, including hands-on MLOps and a track record of taking ML models into production at scale.
Strong experience with ML lifecycle tooling — experiment tracking, observability/monitoring, model registry, versioning, lineage, and reproducibility (e.g., MLflow, Kubeflow, Weights & Biases).
Strong experience with containerization and orchestration (Docker, Kubernetes) — including scaling GPU workloads — and with a major cloud platform (Azure preferred) and its ML services (e.g., Azure ML), using IaC and CI/CD for ML.
Proficiency in Python (and familiarity with Bash) for automation, tooling, and pipeline development.
Preferred / bonus qualifications:
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:
Experience supporting computational biology or bioinformatics pipelines, including protein structure prediction or design tools (e.g., AlphaFold, Boltz/BoltzGen, Chai, RFdiffusion, ProteinMPNN) or molecular simulation.
Experience operating ML in a regulated environment (GxP, SOX, or HIPAA), including model traceability and audit evidence.
Familiarity with LLMOps / agentic frameworks and evaluation tooling (e.g., Langfuse, OpenTelemetry for LLMs).
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 $180,000 - $220,000. 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. #LI-Remote
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.
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].
Danaher is a leading global life sciences and diagnostics innovator, committed to accelerating the power of science and technology to improve human health. We partner with customers around the world to accelerate breakthroughs from idea to impact, moving with the speed and certainty they need to advance life‑changing science. By working side‑by‑side with researchers, scientists, and clinicians, we solve their hardest problems—together, bringing the right expertise, technologies, and partners from across our portfolio to architect the most effective solutions. Through our connected ecosystem of companies operating at global scale, we help customers streamline and integrate their workflows across Life Sciences, Diagnostics, Biotechnology, and beyond—empowering them to achieve results faster, with greater confidence.
Offices: 2200 Pennsylvania Ave NW, 800 W, Washington, District of Columbia 20037, US
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