Senior Devops / Mlops Engineer - Remote Eligible

Senior DevOps/MLOps Engineer

As the leader in animal health, Zoetis is looking to recruit a Senior DevOps/MLOps Engineer into its world-class Veterinary Medicine Research and Development (VMRD) organization to operationalize AI/ML, scientific modeling, and digital twin workloads. You'll build secure, scalable platforms and data pipelines across cloud and on-prem/HPC, partnering closely with biologists and data scientists to translate scientific questions into reliable production systems.

Essential Duties and Responsibilities:

• Build end-to-end DevOps/MLOps foundations: CI/CD for code/data/models, containerization/orchestration, artifact/registry management, and secure configuration.
• Design and operate data engineering pipelines (batch/streaming) with data quality checks, lineage, schema contracts, and governance across lake/warehouse environments.
• Productionize scientific and digital twin workflows into services/APIs and lightweight UIs with reproducibility, versioning, auditability, and compliant deployment.
• Implement scalable training/inference (batch/real-time) with observability, SLIs/SLOs, runbooks, incident response, and automated rollback strategies.
• Run distributed/HPC jobs (including GPU) and optimize storage, throughput, and cost across on-prem and cloud; collaborate with scientists on experiment design, data/compute needs, and validation.

Required Experience/Skills:

• PhD in a quantitative field (computer science, ML, computational biology, applied math) or MS/BS with equivalent senior engineer level experience working in a scientific domain.
• 6+ years building production systems; strong software engineering fundamentals.
• Expert in Python
• Strong experience with a query language such as SQL, MapReduce, and/or Cypher
• Proficiency in one of: C++, Go, Rust, Java, or Scala.
• Docker, Kubernetes, CI/CD (e.g., GitHub Actions), secure artifact/container registries.
• Data pipeline orchestration (e.g., Databricks, Dagster, Kedro); streaming (Kafka or Redis); data modeling with SQL/NoSQL/graph.
• MLOps: experiment tracking and model versioning (e.g., MLflow), model serving and monitoring.
• Cloud (AWS/Azure/GCP) and on-prem/HPC (e.g., Slurm) experience.
• Experience on multidisciplinary projects and teams, including scientists and software engineers, with excellent communication with scientific stakeholders.

Additional Experience/Skills:

• APIs and scientific apps: FastAPI; minimal UIs (Streamlit/React); scientific computing (NumPy, Pandas, SciPy).
• DevOps/IaC: Terraform; GitOps (Argo CD/Flux); Helm/Kustomize; Docker/Kubernetes; secure registries and config.
• Data engineering: dbt and feature stores; Parquet/Delta; schema/lineage with Avro/Protobuf, OpenLineage, Great Expectations.
• Observability/SRE: Prometheus/Grafana; ELK/OpenSearch; OpenTelemetry; SLIs/SLOs and performance profiling/optimization.
• Distributed compute and resilience: Dask, Ray, Spark; HPC/Slurm; GPU scheduling; service mesh (Istio/Linkerd), API gateways, ingress; encryption/secrets/KMS, audit trails, backup/restore, DR.

Job Type:

• Full-time, Remote (US).
• Work hours aligned to US Eastern through US Pacific time zones.

The following base pay range reflects the anticipated base pay for this position if a selected candidate were to be located in Colorado. Base pay may vary based on location and other factors.

Base Pay Range: $105,000 - $128,000

The following base pay range reflects the anticipated base pay for this position if a selected candidate were to be located in California, NJ Remote, NY Remote, or Washington. Base pay may vary based on location and other factors.

Base Pay Range: $118,000 - $145,000

This position is eligible for short-term incentive compensation. The position is also eligible for long-term incentive.

We offer a competitive and comprehensive benefits package, which includes healthcare, dental coverage, and retirement savings benefits along with paid holidays, vacation and disability insurance.