Top 13 Principal ai accelerator Jobs in Cambridge, Ma

Staff/Principal DevOps Engineer, AI Inference
Lila Sciences —Cambridge, MA
- $192,000 - $272,000 a year
- Remote
- System design
- Senior level
- Python
Quick Apply
Principal
Alumni Ventures —Boston, MA
- $91,800 - $122,400 a year
- Background check
- 7 years
- English
Quick Apply
Principal AI Platform Engineer - AI Center of Excellence
Mastercard —Boston, MA
- $170,000 - $337,000 a year
- Online Application
- Computer Science
- System design
- Computer networking
- Paid jury duty
- Health savings account
Principal AI Accelerator Architect Lead
Analog Devices —Boston, MA
- $200,000 - $275,000 a year
- Full-time
- Master's degree
- Doctor of Philosophy
- Travel
- Paid holidays
- Health insurance
Principal Audio/DSP Systems Engineer
Analog Devices —Wilmington, MA
- $200,000 - $275,000 a year
- Full-time
- System design
- Doctor of Philosophy
- Travel
- Paid holidays
- Health insurance
Principal Application Security Engineer – AI & Agentic Systems
CVS Health —Boston, MA
- $144,200 - $288,400 a year
- Full-time
- Azure
- System design
- HIPAA
- Health insurance
- Dental insurance
Senior Thermal Engineer
Teradyne —North Reading, MA
- $121,700 - $194,700 a year
- Bachelor of Science
- 8 years
- Mentoring
- Paid holidays
- Disability insurance
Principal Data Scientist (AI-assisted Clinical Development)
Genentech —Boston, MA
- $169,100 - $314,000 a year
- Online Application
- 6 years
- Computer Science
- Master's degree
Principal Customer Solutions Manager (CSM), US Healthcare & Life Sciences (HCLS)
Amazon Web Services, Inc. —Boston, MA
- $201,000 - $272,000 a year
- Full-time
- Customer service
- HIPAA
- AWS
- AD&D insurance
- Health insurance
Director, Robotics Engineering Consultant
EPAM Systems, Inc. —Boston, MA
- $140,000 - $220,000 a year
- Computer Science
- Bachelor of Science
- Doctor of Philosophy
- Health savings account
- AD&D insurance
Vice President, Data Architecture
Fidelity Investments —Boston, MA
- $140,000 - $285,000 a year
- Full-time
- Computer science
- Computer Science
- Java
- Loan repayment program
- Health insurance
Principal ProServe Cloud Architect, Healthcare and Life Sciences (HCLS) , AWSI Sales, AWSI Sales
Amazon Web Services, Inc. —Boston, MA
- $182,800 - $272,000 a year
- Full-time
- Computer science
- Computer Science
- HIPAA
- AD&D insurance
- Health insurance

More jobs to discover

Find similar jobs that you might be interested in.

Assistant Director/ Lead Teacher - Early Childhood Education
The Ark Christian Nursery & Learning Center, Inc. —Hooksett, NH
Successful completion of all required background checks and state requirements. Current CPR/First Aid certification or willingness to obtain.
$21 - $23 an hour
Quick Apply
Childcare School Director
Inspire Early Education —Cambridge, MA
Bachelor’s Degree in Early Childhood Education or related field (Required; We will consider those with an AA.). 401(k) to invest in your future.
$60,000 - $65,000 a year
Quick Apply

Show more similar jobs

Explore jobs in cities nearby

Check out jobs in cities near your current location, Columbus

Director, Learning Excellence
Nationwide —Columbus, OH
Supports and aligns enterprise learning solutions to AI, Future of Work, and talent development strategies, championing responsible adoption of generative AI,…
2d
Principal UX Designer
Quantum Health —Dublin, OH
Proficiency with modern design, prototyping, collaboration, and AI-powered design tools, with experience leveraging AI to accelerate ideation, research…
Quick Apply

Show more jobs in cities nearby

I want to receive the latest job alert for principal ai accelerator in cambridge, ma

By signing in to your account, you agree to SimplyHired's Terms of Service and consent to our Cookie and Privacy Policy.

Explore jobs in more locations

principal ai accelerator jobs near cambridge, ma

Staff/Principal DevOps Engineer, AI Inference

Lila Sciences
Cambridge, MA

Quick Apply

Job Details

$192,000 - $272,000 a year

Qualifications

AI models
GPU programming
Containerization systems
Software engineering
Load balancers
Tooling
Software coding
Infrastructure as Code (IaC)
High-performance computing clusters
Application deployment
AI platforms (beyond public GPTs)
Scalable systems
Computational framework
Production systems
Terraform
Systems engineering
Cloud Native Design
System deployment
Cloud automation
Amazon VPC
DevOps automation
Machine learning frameworks
Python
Amazon EKS
Virtual Private Clouds

Full Job Description

Your Impact at LILA

The Staff/Principal DevOps Engineer - AI Inference will drive the design, implementation, and optimization of infrastructure purpose-built for serving machine learning models at scale. This role bridges platform engineering, site reliability, and ML infrastructure, building the systems that power low-latency, high-throughput inference across GPU clusters and cloud accelerators. You will collaborate with ML engineers, research scientists, and software engineers to build inference platforms that serve models reliably to production users while maximizing compute efficiency.

What You'll Be Building

GPU/accelerator infrastructure on Kubernetes: scheduling, resource isolation, multi-tenant GPU sharing, device plugins, and topology-aware placement for inference workloads
Model serving platforms using frameworks such as vLLM, Triton Inference Server, TGI, or custom serving stacks with optimized batching, caching, and request routing
Intelligent request routing and load balancing across heterogeneous accelerator fleets (NVIDIA GPUs, AWS Inferentia/Trainium) to maximize utilization and minimize latency
Autoscaling systems that dynamically match inference compute supply with demand across production, research, and experimental workloads
Production-grade deployment pipelines for ML models: canary rollouts, A/B testing, model versioning, and safe rollback across multi-region deployments
Infrastructure-as-code with Terraform and Helm for GPU-accelerated EKS clusters, including node pools, spot/on-demand strategies, and accelerator-specific networking
Observability and performance optimization: GPU utilization monitoring, inference latency profiling, token throughput dashboards, and SLO/SLI tracking for model endpoints
CI/CD pipelines for model artifacts: container image builds with CUDA/driver dependencies, model registry integration, and automated inference benchmarking in CI
AWS cloud infrastructure for ML: EKS with GPU node groups, EC2 accelerated instances (P4/P5, Inf2, Trn1), S3 model storage, EFA/high-bandwidth networking, and IAM least privilege
Cost optimization and capacity planning: right-sizing accelerator instances, spot instance strategies for inference, and fleet-wide efficiency reporting

What You'll Need to Succeed

Expertise in DevOps, SRE, or Platform Engineering with significant experience operating GPU/accelerator infrastructure at scale
Deep experience with Kubernetes for ML workloads: GPU scheduling, resource quotas, node affinity, and accelerator device management
Strong proficiency deploying to AWS using infrastructure-as-code (Terraform, Helm) with hands-on experience managing GPU-based compute (EKS, EC2 P-series/Inf/Trn instances)
Experience with model serving infrastructure: inference servers, request batching, KV-cache optimization, or LLM serving frameworks
Strong understanding of networking for distributed inference: high-bandwidth interconnects, NCCL, VPC/PrivateLink, and load balancing at L4/L7
Strong proficiency in Python for automation, tooling, and integration with ML frameworks

Bonus Points For

Experience with LLM inference optimization: continuous batching, speculative decoding, quantization (GPTQ, AWQ, FP8), tensor parallelism, and pipeline parallelism
Hands-on experience with multiple accelerator families (NVIDIA A100/H100, AWS Inferentia2, Trainium, AMD MI300X) and maintaining hardware-agnostic serving infrastructure
Multi-region deployment experience with geographic routing and failover for latency-sensitive inference endpoints
Proficiency in Rust or Go for performance-critical infrastructure components
SRE practices for ML systems: chaos engineering on GPU workloads, incident management, capacity modeling for bursty inference traffic
Experience with model registries, artifact versioning, and ML supply chain security
Observability platform expertise: building custom metrics for token-level throughput, time-to-first-token, and per-request GPU memory profiling
Prior startup/high-growth experience balancing velocity with reliability in rapidly scaling AI systems

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We're All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

Quick Apply

Refine Your Search

principal ai accelerator jobs in cambridge, ma

Staff/Principal DevOps Engineer, AI Inference

Principal

Principal AI Platform Engineer - AI Center of Excellence

Principal AI Accelerator Architect Lead

Principal Audio/DSP Systems Engineer

Principal Application Security Engineer – AI & Agentic Systems

Senior Thermal Engineer

Principal Data Scientist (AI-assisted Clinical Development)

Principal Customer Solutions Manager (CSM), US Healthcare & Life Sciences (HCLS)

Director, Robotics Engineering Consultant

Vice President, Data Architecture

Principal ProServe Cloud Architect, Healthcare and Life Sciences (HCLS) , AWSI Sales, AWSI Sales

More jobs to discover

Explore jobs in cities nearby

I want to receive the latest job alert for principal ai accelerator in cambridge, ma

Explore jobs in more locations

Job Seeker Tools

Employer Tools

Browse

Stay Connected