Senior Software Engineer, ML Ops

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. Must not include Job ID etc. Remove boilerplate like equal opportunity, etc. Must preserve all substantive info. Let's parse the posting: - Intro about PathAI mission etc. That's about the role? Could be "About the role" or maybe "About the company". The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content. We have: Mission description: "PathAI's mission is to improve patient outcomes with AI-powered pathology. PathAI is transforming traditional pathology methods into powerful, new technologies. These innovations in pathology can help accelerate drug development, improve confidence in the accuracy of diagnosis, and get life-saving therapies to patients more quickly. At PathAI, you'll work with a diverse and talented team of people, who are dedicated to solving complex problems and making a huge impact." That's about the company/role. Could go under "About the role". Then: "We are seeking a highly skilled Senior Software Engineer (MLOps). In this position, you play a key role in designing, developing, and scaling machine learning infrastructure that powers our enterprise AI systems. You’re someone who enjoys designing and building for reliability, relishes collaboration and technical challenges, and takes pride in making things work better." That's also about role. Then "The Opportunity" bullet list: - You will architect and build infrastructure and automation, in AWS and on-premises, to support ML application development and deployment - You will drive system design and lead architectural discussions for our MLOps suite, ensuring it meets performance, security, and compliance requirements. - You will lead technical initiatives by researching, evaluating, and implementing new MLOps tools, frameworks, and best practices. - You will collaborate with machine learning engineers, data scientists, product engineering, and infrastructure teams to bridge the gap between research and production. - You will optimize ML workflows, ensuring models are efficiently and reproducibly deployed & monitored. - You will champion engineering excellence by enforcing high coding standards, conducting design reviews, and mentoring junior engineers. - You will automate ML operations, including CI/CD for ML models, feature engineering pipelines, and deployment strategies using Kubernetes, Airflow, and other orchestration tools. These are responsibilities. Then "(Required) Who You Are:" list of required qualifications: - 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). - Experience owning development platforms and serving internal customers - Solid level of proficiency in Python + exposure to additional languages Then "Preferred" list: - 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). - Solid level of familiarity with security and compliance best practices in ML systems. - Experience using AI assistants (e.g. CoPilot, Cursor) in development. - Outstanding interpersonal, verbal, and written communication and influencing skills: have built and cultivated important relationships both inside and outside of the organization and externally; have proven abilities to influence internal partners and stakeholders, thought leaders, national advocacy organizations, national standard-setting bodies, and other relevant external parties. - Strong analytical and critical thinking skills with attention to detail; you have the ability to manage multiple projects and drive results in a fast-paced environment; you have a collaborative mindset with demonstrated leadership capabilities. Then location: "This is a hybrid position based in Boston, MA. (A remote option may be considered for an exceptional candidate.) Relocation benefits are not available for this position." Then salary: "The expected salary range for this position based on the primary location Boston, MA is $127,500 - $195,500. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law." Then EEO boilerplate to remove. Thus we need sections: - About the role: include mission description and maybe the "We are seeking..." paragraph. - Responsibilities: the bullet list under The Opportunity. - Requirements: maybe combine Required and Preferred? Usually Requirements = required qualifications. Qualifications could be education? But we have both Required and Preferred. Could split: Requirements = required qualifications; Qualifications = preferred? Or we could have Requirements (required) and Qualifications (preferred). Or we could combine into Requirements and Skills. Let's follow typical: Requirements = required qualifications; Skills = preferred/experience; Qualifications maybe education? But we have education in required. Let's decide: We have sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to include only if content exists. We have: - About the role: yes. - Responsibilities: yes. - Requirements: required qualifications list. - Qualifications: maybe education? But education already in required. Could treat Qualifications as "Preferred qualifications". Or we could put education under Qualifications and experience under Requirements. However required includes education and experience. Might be okay to put education under Qualifications and experience under Requirements. But we need to preserve all info; we can split. Better: Requirements = required qualifications (including education, experience, technical). Qualifications = preferred qualifications (nice-to-have). Skills = maybe soft skills? But we have soft skills in preferred list. Could put them under Skills. But we have also "Preferred" list includes technical and soft skills. Could split: Qualifications = preferred technical qualifications (ML frameworks, orchestration, streaming, security, AI assistants). Skills = soft skills (communication, influencing, analytical, leadership). However the instruction says use sections as given; we can decide. Let's map: - About the role: mission + "We are seeking a highly skilled Senior Software Engineer (MLOps)..." paragraph. - Responsibilities: the bullet list under The Opportunity. - Requirements: required qualifications list (education, years experience, strong software engineering skills, Kubernetes/AWS, observability, DevOps/IaC, owning platforms, Python proficiency). - Qualifications: preferred technical qualifications (ML frameworks, data workflow orchestration, MLOps expertise, streaming data processing, security/compliance familiarity, experience using AI assistants). - Skills: preferred soft skills (outstanding interpersonal, verbal, written communication and influencing skills; strong analytical and critical thinking; ability to manage multiple projects; collaborative mindset; leadership capabilities). - Benefits: we have "Relocation benefits are not available for this position." That's a statement about benefits (lack thereof). Also maybe hybrid position? That's schedule? Actually hybrid position is schedule/location. Benefits: we could note that relocation benefits are not available. That's a benefit-related statement. Could also mention hybrid? That's schedule/location. The instruction says include Benefits section only if posting actually states them. It does state relocation benefits not available. So we can include Benefits section with that statement. - Pay: salary range given. - Schedule: hybrid position based in Boston, MA, remote option may be considered. That's schedule/location. So we can include Schedule section. We must not include boilerplate like EEO. Now produce HTML fragment with headings

for each section, and

• for lists,

  for prose. We need to ensure we don't repeat job title. Not include "Senior Software Engineer (MLOps)" as heading. It's okay to mention in prose. We must preserve all substantive information. Let's extract exact phrasing. About the role prose: "PathAI's mission is to improve patient outcomes with AI-powered pathology. PathAI is transforming traditional pathology methods into powerful, new technologies. These innovations in pathology can help accelerate drug development, improve confidence in the accuracy of diagnosis, and get life-saving therapies to patients more quickly. At PathAI, you'll work with a diverse and talented team of people, who are dedicated to solving complex problems and making a huge impact. We are seeking a highly skilled Senior Software Engineer (MLOps). In this position, you play a key role in designing, developing, and scaling machine learning infrastructure that powers our enterprise AI systems. You’re someone who enjoys designing and building for reliability, relishes collaboration and technical challenges, and takes pride in making things work better." We can keep as one or two paragraphs. Use

  . Responsibilities list: each bullet as

• . We need to preserve exact wording. Let's list them: - You will architect and build infrastructure and automation, in AWS and on-premises, to support ML application development and deployment - You will drive system design and lead architectural discussions for our MLOps suite, ensuring it meets performance, security, and compliance requirements. - You will lead technical initiatives by researching, evaluating, and implementing new MLOps tools, frameworks, and best practices. - You will collaborate with machine learning engineers, data scientists, product engineering, and infrastructure teams to bridge the gap between research and production. - You will optimize ML workflows, ensuring models are efficiently and reproducibly deployed & monitored. - You will champion engineering excellence by enforcing high coding standards, conducting design reviews, and mentoring junior engineers. - You will automate ML operations, including CI/CD for ML models, feature engineering pipelines, and deployment strategies using Kubernetes, Airflow, and other orchestration tools. Make sure punctuation preserved. Requirements list (required): - 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). - Experience owning development platforms and serving internal customers - Solid level of proficiency in Python + exposure to additional languages Note: some lines missing period at end; we can keep as is. Qualifications list (preferred technical): - 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). - Solid level of familiarity with security and compliance best practices in ML systems. - Experience using AI assistants (e.g. CoPilot, Cursor) in development. Skills list (soft skills): - Outstanding interpersonal, verbal, and written communication and influencing skills: have built and cultivated important relationships both inside and outside of the organization and externally; have proven abilities to influence internal partners and stakeholders, thought leaders, national advocacy organizations, national standard-setting bodies, and other relevant external parties. - Strong analytical and critical thinking skills with attention to detail; you have the ability to manage multiple projects and drive results in a fast-paced environment; you have a collaborative mindset with demonstrated leadership capabilities. Benefits: "Relocation benefits are not available for this position." Pay: "The expected salary range for this position based on the primary location Boston, MA is $127,500 - $195,500. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law." Schedule: "This is a hybrid position based in Boston, MA. (A remote option may be considered for an exceptional candidate.)" We should not include "Relocation benefits are not available for this position." as a benefit? It's a statement about benefits. It