Level

PathAI

Senior/Staff Software Engineer, ML Ops

PathAI is hiring a Senior/Staff Software Engineer, ML Ops in Boston, United States. It pays $128k-$196k a year and Level rates it ; you can apply on Level.

AI in this role

copilotpytorchscikit-learncursor
ml-ops

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.

The Opportunity

  • 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.

Who You Are:
(Required)

  • You have a BS or Master’s in Computer Science, Computer Engineering, Software Engineering or closely related field.
  • You have 5+ years of software engineering experience for Senior or 8+ years for Staff, with a focus on building production-grade frameworks or applications
  • You have strong software engineering skills in complex, multi-language systems and experience with scalable backend architecture.
  • You have experience with Kubernetes and cloud computing platforms (AWS preferred).
  • You have experience with observability and monitoring tools (e.g., Prometheus, Grafana, Datadog).
  • You have a solid understanding of DevOps principles and infrastructure-as-code (Helm, Terraform).
  • You have experience owning development platforms and serving internal customers
  • You have a solid level of proficiency in Python + exposure to additional languages

Preferred:

  • You have experience with ML frameworks like PyTorch or Scikit-learn.
  • You have experience with data workflow orchestration frameworks (e.g., Airflow, Kubeflow).
  • You have expertise in MLOps principles, including model lifecycle management, feature stores, model monitoring, and CI/CD for ML.
  • You have experience with streaming data processing (Kafka, Flink, or Spark Streaming).
  • You have a solid level of familiarity with security and compliance best practices in ML systems.
  • You have experience using AI assistants (e.g. CoPilot, Cursor) in development.
  • You have 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.
  • You have 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.

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.

The expected salary range for this position based on the primary location Boston, MA is $127,500 - $195,500 at the Senior level and $146,250 - $224,250 at the Staff level.  Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law.  

PathAI is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

How we rate this

Senior/Staff Software Engineer, ML Ops at PathAI rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsCopilotPyTorchscikit-learnCursor

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Walk me through how you've used Copilot in your day-to-day work.
  3. What are the limits of PyTorch that you've run into, and how did you work around them?
  4. What's a project where you used scikit-learn hands-on?
  5. Walk me through how you've used Cursor in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: ML Ops, Copilot, PyTorch, scikit-learn, and Cursor. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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