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Remote Gpu Programming Jobs in Colorado (NOW HIRING)

In Tandem

AI Engineer

Denver, CO · On-site +1

$100K - $135K/yr

Remote USA - In Tandem Compensation: $100,000 - $135,000 / year Description At In Tandem, we build ... Run the inference serving layer on our own GPU hardware: choose and tune the serving stack (vLLM ...

SciTec

Senior Numerical Algorithm Software Engineer

Boulder, CO · On-site +1

$127K - $167K/yr

... GPU acceleration, memory optimization) * Knowledge of DoD or Intelligence Community mission systems, especially related to remote sensing or space-based sensors * Experience transitioning algorithms ...

VDURA

Systems Engineer, Platform

Niwot, CO · On-site +1

Familiarity with GPU-accelerated systems and AI infrastructure requirements * Experience with ... However, we are open to remote candidates who meet the qualifications and can work effectively from ...

VDURA

Systems Engineer, Platform

Longmont, CO · On-site +1

Familiarity with GPU-accelerated systems and AI infrastructure requirements * Experience with ... However, we are open to remote candidates who meet the qualifications and can work effectively from ...

Stackinfra

Director, Solutions Engineering

Denver, CO · Remote

... cooled GPU environments and other high-density workload needs. * Translate Complex Needs into ... Location: Remote * Travel: 15-30% * Benefits: Healthcare, Dental Care, Vision Insurance, Life ...

Invoca

Senior ML Engineer

Denver, CO · On-site +1

$107K - $147K/yr

... GPU infrastructure. Profile and tune for low latency and high throughput, and build robust ... Familiarity with RLHF or preference training is a bonus 📍 Location This is a remote-first role.

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Remote Gpu Programming information

What are some common challenges faced by professionals in remote GPU programming roles, and how can they be addressed?

Remote GPU programming roles often involve unique challenges such as managing high-latency connections to remote servers, troubleshooting hardware-specific issues without physical access, and ensuring code compatibility across different GPU architectures. Effective communication with distributed teams is crucial, as is using robust remote debugging tools and version control systems. Staying proactive with documentation and regularly syncing with team members can help address these obstacles and support successful project delivery.

What is remote GPU programming?

Remote GPU programming refers to the practice of developing and running code that utilizes graphics processing units (GPUs) on computers or servers that are accessed over a network, rather than on your local machine. This approach allows developers to leverage powerful, often cloud-based, GPU resources to handle computationally intensive tasks like machine learning, scientific simulations, or rendering without needing specialized hardware themselves. It often involves using remote desktop tools, cloud platforms, or custom APIs to access and manage GPU resources remotely.

What are the key skills and qualifications needed to thrive as a Remote GPU Programmer, and why are they important?

To thrive as a Remote GPU Programmer, you need in-depth knowledge of parallel computing, proficiency in programming languages like C/C++, and experience with GPU architectures, often backed by a degree in computer science or a related field. Familiarity with technical tools such as CUDA, OpenCL, and GPU profiling/debugging systems is commonly required, along with certifications in GPU programming or high-performance computing. Strong problem-solving abilities, self-motivation, and effective remote communication skills help individuals excel in distributed teams. These competencies are crucial for efficiently developing and optimizing GPU-accelerated applications while collaborating across remote environments.
What are the most commonly searched types of Gpu Programming jobs in Colorado? The most popular types of Gpu Programming jobs in Colorado are:
What are popular job titles related to Remote Gpu Programming jobs in Colorado? For Remote Gpu Programming jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Gpu Programming jobs in Colorado look for? The top searched job categories for Remote Gpu Programming jobs in Colorado are:
What cities in Colorado are hiring for Remote Gpu Programming jobs? Cities in Colorado with the most Remote Gpu Programming job openings:
Remote Gpu Programming jobs near you

AI Engineer

In Tandem

Denver, CO • On-site, Remote

$100K - $135K/yr

Full-time

Retirement, PTO

Re-posted 6 days ago

Job description

AI Engineer
Department: Data Engineering
Employment Type: Permanent - Full Time
Location: Remote USA - In Tandem
Compensation: $100,000 - $135,000 / year
Description
At In Tandem, we build technology that helps families manage everyday routines and navigate life's biggest transitions. Through our four brands-OurFamilyWizard, Cozi, FamilyWall, and Custody Navigator-we help families stay organized, communicate well, and foster healthy childhoods.
We believe technology should strengthen relationships and make daily coordination less complicated. Everything we create is designed to lighten the mental load, reduce conflict, and support families through big and small moments.
If you want your work to make a real difference in the daily lives of parents and kids, In Tandem is the place where your impact will truly matter.
As our AI Engineer, you'll keep the AI infrastructure our products and teams run on fast, efficient, and reliable, and you'll build with it. You'll run and optimize our self-hosted inference stack on our own GPU hardware, build the internal platform our employees work through, and ship user-facing agents inside the apps. Your work spans OurFamilyWizard, Cozi, and FamilyWall, and the platforms that power how we build.
This is a hands-on technical role at its core: you own the technical side of running our models on our own hardware. But it's not siloed, and we don't want it to be. We're looking for someone who also wants to pick up app-layer work and ship product-facing features, and does both well.
What you will accomplish:
Run and optimize our self-hosted inference stack
  • Run the inference serving layer on our own GPU hardware: choose and tune the serving stack (vLLM, SGLang, TensorRT-LLM) for high throughput and low latency.
  • Optimize aggressively: tensor parallelism, quantization (FP8, AWQ, GPTQ), KV-cache and prefix caching, continuous batching, speculative decoding, concurrency tuning.
  • Serve multiple models and features off shared hardware: multi-LoRA, routing, and request scheduling that balances internal workloads against latency-sensitive product traffic.

Keep our AI fast, efficient, and observable
  • Make our AI workloads efficient: improve latency, throughput, and GPU utilization so we get the most out of what we run.
  • Build the visibility: instrument performance and usage across our AI surfaces so there's clear data on how everything is running.
  • Surface the technical tradeoffs (performance, latency, efficiency) so the people making the calls have what they need to make them.

Build AI features and proactive agents
  • Ship the in-app agent layer that helps families coordinate: proactive nudges, smart suggestions, agents that summarize, draft, schedule, and act for busy parents.
  • Build the substrate underneath: tools, memory, orchestration, guardrails, and evaluation harnesses, integrated cleanly with production APIs alongside our architecture team.
  • Work in nimble pairs with feature owners, standing up whatever's needed to test an idea, including a vibe-coded UI when that's the fastest path to a real customer. Ship rough, learn fast, harden what works.

Who you are:
  • Technical and hands-on with infrastructure: you like running real systems on real hardware and keeping them fast and reliable.
  • A full-stack builder who wants the app layer too: you don't want to be boxed into infra. When a feature needs shipping, you want to pick it up and ship it, not just hand it off.
  • Performance-minded: you treat latency, throughput, and efficiency as things to engineer deliberately.
  • Rapid-prototyping and AI-first, with modern tooling (Claude Code, agent SDKs) part of your craft.
  • Motivated by work that matters. Families rely on these products during real moments in their lives.

What you bring:
  • 5+ years shipping production software, including meaningful applied AI or ML work.
  • Demonstrated experience running and optimizing self-hosted LLMs on dedicated multi-GPU hardware: a serving stack (vLLM, SGLang, or TensorRT-LLM) and the optimization that comes with it (tensor parallelism, quantization, batching, KV cache).
  • A track record of optimizing inference performance and efficiency (latency, throughput, GPU utilization).
  • Strong Python and engineering fundamentals, with the full-stack range to stand up a quick UI, and the genuine desire to work app-layer features and not only infra.
  • Hands-on with agent frameworks (Claude Agent SDK, LangGraph, or similar), LLM APIs, embeddings, and RAG.
  • Comfortable with AWS and the devops this role owns: Docker, CI/CD, monitoring, and observability.
  • Experience building internal tooling or platforms others depend on. Bonus for Slack apps, MCP, or agent orchestration at team scale.

Why Join?
We're redefining family technology.
In Tandem brings together a growing portfolio of trusted tools that support families, and the professionals who guide them, through the moments that matter most. We bring clarity to chaos and stability to daily family life, helping parents feel less stressed so kids can have healthier childhoods.
Scale meets startup energy.
With more than 20 years of impact and a strong market presence, we're entering a bold new chapter of growth. We have the foundation, the momentum, and the ambition to go further: expanding our reach, deepening our impact, and elevating the tools families and professionals rely on every day.
Purpose-driven. Performance-focused. People-first.
Our culture is rooted in accountability, curiosity, and collaboration. We value diverse perspectives, thoughtful problem-solving, and teammates who care deeply about building something that matters.
How we support you:
  • Medical: In Tandem pays 100% of the premium for employees AND 99% for all additional family members
  • 401k: Up to a 4% match with immediate vesting
  • Paid leave for all new parents
  • Learning & Development stipend for employees
  • Paid Time Off: 11 Holidays + Winter Break (3 Days) + Volunteer Time Off (1 Day) + Floating Holiday (1 Day)
  • Personal Time Off: 15 days for 0-1 years of employment, 20 days 1-3 years of employment
  • Supportive and flexible working environment - work from anywhere!

Come As You Are!
In Tandem provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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