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Remote Nvidia Deep Learning Jobs in Boston, MA (NOW HIRING)

Gradient AI

Staff Data Scientist

Boston, MA · On-site +1

$160K - $195K/yr

This is a fully remote opportunity with hybrid available to those local to Boston. Gradient AI ... Leverage the best of modern deep learning & large language models with traditional data science ...

Gradient AI

Senior Data Scientist

Boston, MA · On-site +1

$140K/yr

This is a fully remote opportunity with hybrid available to those local to Boston. Gradient AI ... Leverage the best of modern deep learning & large language models with traditional data science ...

Adidev Technologies Inc

ML/AI Engineers

Boston, MA · Remote

Hands-on experience with Deep Learning, LLM, Python, TensorFlow, PyTorch and other AI frameworks ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Harvard University

Senior Research Software Engineer

Cambridge, MA · On-site +1

$135K - $177K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Hybrid / primarily remote within approved payroll states Qualifications Basic Qualifications are ... Proven experience in deep learning at scale, familiarity with the "alphabet soup" of distributed ...

OneStudyTeam

Senior Machine Learning Engineer

Boston, MA · Remote

$140K - $190K/yr

Deep ML/AI knowledge: Strong understanding of machine learning fundamentals (model selection ... LI-Remote We value diversity and believe the unique contributions each of us brings drives our ...

Ascend Learning

Sr Solutions Engineer

Burlington, MA · On-site +1

$60 - $77.50/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... remote workers in cities across the U.S., Ascend Learning was recognized by Newsweek and Plant-A ... Develop deep understanding of leader specific challenges, including: * Nurse staffing shortages and ...

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All JobsNvidia Deep Learning JobsRemote Nvidia Deep Learning JobsRemote Nvidia Deep Learning Jobs in Boston, MA

Remote Nvidia Deep Learning information

See Boston, MA salary details

$11.9K

$91.1K

$152.1K

How much do remote nvidia deep learning jobs pay per year?

As of Aug 16, 2026, the average yearly pay for remote nvidia deep learning in Boston, MA is $91,133.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,200.00 and $151,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Nvidia Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Nvidia Deep LearningRemote Machine Learning Engineer
Required CredentialsDeep learning certifications, Nvidia GPU expertise, programming skills in Python and CUDAMachine learning certifications, Python, data analysis, model deployment skills
Work EnvironmentRemote, GPU-intensive tasks, AI research, model trainingRemote, data processing, model development, deployment
Industry UsageAI research labs, tech companies, autonomous vehiclesTech firms, finance, healthcare, e-commerce

Remote Nvidia Deep Learning focuses on developing AI models using Nvidia GPUs and CUDA, often in research or AI-specific roles. Remote Machine Learning Engineers work on building and deploying machine learning models across various industries. While both roles require programming and data skills, Nvidia Deep Learning emphasizes GPU expertise and AI research, whereas Machine Learning Engineers focus on broader model deployment and application.

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For Remote Nvidia Deep Learning jobs in Boston, MA, the most frequently searched job titles are:

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Staff Engineer, Inference Optimizations

DigitalOcean

Boston, MA • Remote

$191K - $239K/yr

Full-time

Posted 23 days ago

Job description

DigitalOcean is seeking a Senior Engineer 2 to play a key technical role in our AI Inference Optimization team. DigitalOcean aims to be the Inference Cloud of choice for digitally native companies and you will help ensure we can offer the industry-leading performance for our inference services. You will be responsible for the architectural decisions that maximize throughput and minimize latency for the world's most advanced large models. As an IC leader, you will act as a force multiplier for the engineering organization, solving the most complex bottlenecks in memory bandwidth and compute utilization while guiding the technical roadmap for our high-performance inference fleet.

What You'll Do:
  • Performance Architecture: Lead the technical strategy for benchmarking and performance optimizations at the inference engine and GPU kernel layers, ensuring our infrastructure extracts maximum value from every TFLOP.
  • Deep-Dive Optimization: Engineer solutions for complex performance issues, including attention layer optimizations, memory and precision management, and advanced parallelization across multi-node GPU clusters. 
  • Technological Innovation: Proactively implement cutting-edge optimization techniques to keep DigitalOcean at the forefront of the Gen AI landscape. Some examples of projects you may work on:
    • Improving batch size performance using AMD's AITER library for AMD MI355X - identify and tune AITER's CK (composable kernel) or ASK (assembly) to optimize FP8 / BF16 
    • Identify kernel fusion opportunities for GLM-5 kernels for different layers of the Transformer block (FlashAttention, RMS Norm)
    • Tune expert gateway router kernels for MoE models like Qwen3-235B, DeepSeek V3, GLM-5 etc
  • Hardware & Ecosystem Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton), advising on hardware procurement and software integration.
  • Precision Optimization: Develop and deploy state-of-the-art quantization techniques (FP8, INT8, and experimental FP4) to double throughput without losing accuracy.
  • Technical Mentorship: Lead by example through high-quality code and design reviews, elevating the technical bar for the team without the administrative overhead of direct management.
  • Strategic Collaboration: Partner with Product Management and TPMs to translate "theoretical hardware limits" into "shippable product features," ensuring our platform is both powerful and developer-friendly.
  • Community Leadership: Maintain a strong presence in the GPU infrastructure and model performance optimization communities, contributing to and integrating the best of open-source AI.
What You'll Bring to DigitalOcean:
  • Technical Depth: 5+ years of experience in high-performance computing or AI infrastructure, with a proven track record of solving compute utilization and memory bandwidth bottlenecks.
  • Gen AI Literacy: Deep familiarity with the Gen AI (LLM, VLM, LMM) landscape, including the specific quirks and architectural requirements of major model families.
  • Optimization Expert: Hands-on experience with attention-layer optimizations and parallelization strategies across distributed GPU environments.
  • Hardware Fluency: Comprehensive understanding of NVIDIA and AMD GPU architectures and their respective software ecosystems (CUDA, ROCm, etc.).
  • Open Source Mastery: Extensive experience integrating, building with, and contributing to open-source software projects.
  • Systems Design: Excellent system design skills, particularly related to low-level GPU programming - optimization, memory access patterns, and parallel execution.
  • Leadership through Influence: Experience acting as a technical lead, driving design and delivery through cross-functional alignment and expert-level delegation.
  • Low-Level Mastery: Deep understanding of GPU architectures (SMs, Warp scheduling, Tensor Cores).
  • The Toolkit: Expert-level Triton or CUDA. If you've contributed to the Triton compiler or wrote custom CUDA kernels for a major LLM, we want you.
Compensation Range: 
  • $191,200 - $239,000

*This is a remote role

JR: 2026-7625

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