or apply directly on PathAI's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 4 days PathAI's roles stay open a median of 9 days
- Reposted
- No
- Salary listed
- Yes 100% of PathAI's roles list one
- Ghost-job risk at PathAI
- low 1 stale, 4 reposted of 9 open
- Hiring momentum
- 20 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from PathAI's own greenhouse board since 2026-08-03. Full hiring picture for PathAI.
About this role
As a Senior Software Engineer in ML Ops at PathAI, you will design, develop, and scale machine learning infrastructure to support AI systems in pathology. Your role involves leading architectural discussions, optimizing ML workflows, and automating operations using tools like Kubernetes and Airflow. Collaboration with machine learning engineers and data scientists is key to bridging research and production, while also mentoring junior engineers and ensuring high coding standards.
- benefits
- 1/5
- freshness
- 5/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 5/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of PathAI as an employer.
What you need
- BS or Master’s in Computer Science, Computer Engineering, Software Engineering or closely related field
- 5+ years of software engineering experience with a focus on building production-grade frameworks or applications
- Strong software engineering skills in complex, multi-language systems and experience with scalable backend architecture
- Experience with Kubernetes and cloud computing platforms (AWS preferred)
- Experience with observability and monitoring tools (e.g., Prometheus, Grafana, Datadog)
- Solid understanding of DevOps principles and infrastructure-as-code (Helm, Terraform)
Nice to have
- Experience with ML frameworks like PyTorch or Scikit-learn
- Experience with data workflow orchestration frameworks (e.g., Airflow, Kubeflow)
- Expertise in MLOps principles, including model lifecycle management, feature stores, model monitoring, and CI/CD for ML
- Experience with streaming data processing (Kafka, Flink, or Spark Streaming)
- Familiarity with security and compliance best practices in ML systems
Worth weighing
- Hybrid position with a possibility of remote work for exceptional candidates
- No relocation benefits available
- Salary range provided but actual pay depends on experience and qualifications
Summarised from PathAI's posting. Read the full original.
Listed by PathAI on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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