Machine Learning Engineer working on next - generation agentic AI platform at Salesforce. Collaborate with teams to innovate and design impactful AI systems for customers.
About the role
- Senior Software Engineer designing and developing MLOps infrastructure for AI pathology at PathAI. Collaborating with teams to optimize ML workflows and automate operations.
Responsibilities
- Architect and build infrastructure and automation, in AWS and on-premises, to support ML application development and deployment
- Drive system design and lead architectural discussions for our MLOps suite, ensuring it meets performance, security, and compliance requirements
- Lead technical initiatives by researching, evaluating, and implementing new MLOps tools, frameworks, and best practices
- Collaborate with machine learning engineers, data scientists, product engineering, and infrastructure teams to bridge the gap between research and production
- Optimize ML workflows, ensuring models are efficiently and reproducibly deployed & monitored
- Champion engineering excellence by enforcing high coding standards, conducting design reviews, and mentoring junior engineers
- Automate ML operations, including CI/CD for ML models, feature engineering pipelines, and deployment strategies using Kubernetes, Airflow, and other orchestration tools.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
- 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)
- Understanding of DevOps principles and infrastructure-as-code (Helm, Terraform)
- Experience owning development platforms and serving internal customers
- Proficiency in Python + exposure to additional languages
Benefits
- Health insurance
- Flexible work arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
FI
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