AI Infrastructure Engineer

Work set-up: 
Full Remote
Contract: 
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Offer summary

Qualifications:

Strong experience in deploying machine learning models in production., Deep understanding of container orchestration and distributed systems architecture., Expertise in Kubernetes administration, including custom resource definitions and cluster management., Experience developing APIs and managing distributed systems for batch and real-time workloads..

Key responsibilities:

  • Design, deploy, and maintain scalable Kubernetes clusters for AI inference and training.
  • Develop and optimize ML model serving infrastructure for high performance.
  • Collaborate with ML and product teams to scale backend infrastructure and optimize compute efficiency.
  • Enhance GPU utilization and build robust model API orchestration systems.

Abridge logo
Abridge Startup https://abridge.com/
11 - 50 Employees
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Job description

About Abridge

Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AIpowered platform was purposebuilt for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.

Our enterprisegrade technology transforms patientclinician conversations into structured clinical notes in realtime, with deep EMR integrations. Powered by Linked Evidence and our purposebuilt, auditable AI, we are the only company that maps AIgenerated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.

We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the SoHo neighborhood of New York, the Mission District in San Francisco, and East Liberty in Pittsburgh.

The Role

As an AI Infrastructure Engineer at Abridge, you’ll play a pivotal role in building and optimizing the core infrastructure that powers our machine learning models. Your work will be instrumental in enhancing the scalability, efficiency, and performance of our AIdriven solutions. You will work with our Infrastructure and Research teams to build, deploy, optimize and orchestrate across our AI models.

What Youll Do

  • Design, deploy and maintain scalable Kubernetes clusters for AI model inference and training

  • Develop, optimize, and maintain ML model serving and training infrastructure, ensuring highperformance and lowlatency.

  • Collaborate with ML and product teams to scale backend infrastructure for AIdriven products, focusing on model deployment, throughout optimization, and compute efficiency.

  • Optimize computeheavy workflows and enhance GPU utilization for ML workloads.

  • Build a robust model API orchestration system

  • Collaborate with leadership to define and implement strategies for scaling infrastructure as the company grows, ensuring longterm efficiency and performance.

    • What You’ll Bring

      • Strong experience in building and deploying machine learning models in production environments.

      • Deep understanding of container orchestration and distributed systems architecture

      • Expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management

      • Experience developing APIs and managing distributed systems for both batch and realtime workloads

      • Excellent communication skills, with the ability to interface between research and product engineering

        • Bonus Points If

          Expertise with model serving frameworks such as NVIDIA Triton Server, VLLM, TRTLLM and so on.

          • Expertise with ML toolchains such as PyTorch, Tensorflow or distributed training and inference libraries.

          • Familiarity with GPU cluster management and CUDA optimization

          • Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices

          • Experience with container registries, image optimization, and multistage builds for ML workloads

          • Experience orchestrating across ASR models or LLM models for building various GenAI applications

            • Why Work at Abridge?

              At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month.

              Joining Abridge means stepping into a fastpaced, highgrowth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business.

              Beyond individual impact, you will have the opportunity to work alongside a team of curious, highachieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients.

              We’re committed to supporting your growth, both professionally and personally. Whether its flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life.

              If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you.

              How we take care of Abridgers:
              • Generous Time Off: 13 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employees.

              • Comprehensive Health Plans: Medical, Dental, and Vision plans for all fulltime employees. Abridge covers 100% of the premium for you and 75% for dependents. If you choose a HSAeligible plan, Abridge also makes monthly contributions to your HSA.

              • Paid Parental Leave: 16 weeks paid parental leave for all fulltime employees.

              • 401k and Matching: Contribution matching to help invest in your future.

              • Pretax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.

              • Learning and Development Budget: Yearly contributions for coaching, courses, workshops, conferences, and more.

              • Sabbatical Leave: 30 days of paid Sabbatical Leave after 5 years of employment.

              • Compensation and Equity: Competitive compensation and equity grants for full time employees.

              • ... and much more!

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Experience

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English
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Other Skills

  • Communication

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