PathAI
Employer Industry: AI-Powered Healthcare Technology
Why Consider this Job Opportunity
Opportunity for career advancement and growth within the organization
Supportive and collaborative work environment
Chance to make a significant impact on patient outcomes through innovative technology
Engage in exciting technical challenges and work with diverse teams
Competitive salary based on experience and skills
What to Expect (Job 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 the MLOps suite, ensuring it meets performance, security, and compliance requirements
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 and monitored
Champion engineering excellence by enforcing high coding standards, conducting design reviews, and mentoring junior engineers
What is Required (Qualifications)
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)
Proficiency in Python with exposure to additional languages
How to Stand Out (Preferred Qualifications)
Exposure to 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 and CI/CD for ML
Familiarity with security and compliance best practices in ML systems
Use of AI assistants (e.g., CoPilot, Cursor) in development
We prioritize candidate privacy and champion equal‑opportunity employment. Central to our mission is our partnership with companies that share this commitment. We aim to foster a fair, transparent, and secure hiring environment for all. If you encounter any employer not adhering to these principles, please bring it to our attention immediately.
We are not the EOR (Employer of Record) for this position. Our role in this specific opportunity is to connect outstanding candidates with a top‑tier employer.
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Why Consider this Job Opportunity
Opportunity for career advancement and growth within the organization
Supportive and collaborative work environment
Chance to make a significant impact on patient outcomes through innovative technology
Engage in exciting technical challenges and work with diverse teams
Competitive salary based on experience and skills
What to Expect (Job 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 the MLOps suite, ensuring it meets performance, security, and compliance requirements
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 and monitored
Champion engineering excellence by enforcing high coding standards, conducting design reviews, and mentoring junior engineers
What is Required (Qualifications)
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)
Proficiency in Python with exposure to additional languages
How to Stand Out (Preferred Qualifications)
Exposure to 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 and CI/CD for ML
Familiarity with security and compliance best practices in ML systems
Use of AI assistants (e.g., CoPilot, Cursor) in development
We prioritize candidate privacy and champion equal‑opportunity employment. Central to our mission is our partnership with companies that share this commitment. We aim to foster a fair, transparent, and secure hiring environment for all. If you encounter any employer not adhering to these principles, please bring it to our attention immediately.
We are not the EOR (Employer of Record) for this position. Our role in this specific opportunity is to connect outstanding candidates with a top‑tier employer.
#J-18808-Ljbffr