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Benefits & Perks
•Parental leave
•Generous paid time off and holidays
•401(k) matching
•Comprehensive health, dental, and vision insurance
•Parental Leave
•Healthcare
Required Skills
Node.js
TypeScript
PostgreSQL
ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products.
THE OPPORTUNITY
We are looking for early-career Software Engineers to join our team in Vancouver, BC. This is a specialized role sitting at the intersection of high-performance computing (HPC) and Large Language Model (LLM) engineering. You will be responsible for building the automated "speedometer and diagnostic" suite for our next-generation AI infrastructure.
In this role, you won’t just be using models; you will be tearing them apart to see how they run on the metal. You will build tools that measure GPU FLOPS, stress-test Infini Band clusters, and define the benchmarks that ensure our systems are production-ready.
RESPONSIBILITIES
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Performance Benchmarking: Run and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites for specific workloads (e.g., long-context window, KV cache reuse).
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Infrastructure Validation: Create automated acceptance tests for new GPU clusters across x86 and ARM systems, measuring GPU memory bandwidth, networking throughput, and multi-node networking performance.
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Model Dev Experience: Develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces). You will ensure the team has seamless, high-performance "dev machines" optimized for model experimentation.
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Tool Development: Build and contribute to tools such as InferenceMAX and genai-bench to automate model evaluation and optimization.
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Deep Hardware Profiling: Use Py Torch Profiler and NVIDIA Nsight Systems to collect performance profiles, identify bottlenecks, and debug the NVIDIA compute/networking stack.
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Monitoring & Observability: Develop real-time dashboards and alerts to monitor system health, model startup times, and runtime performance.
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Continuous Integration: Automate performance testing via CI/CD pipelines to catch regressions in model setups before they hit production.
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Optimization Automation: Build tools to find the "Pareto frontier"—identifying the absolute best configuration (latency vs. cost vs. quality) for a given model and workload.
WHAT WE'RE LOOKING FOR
This is a fresher-friendly
role. We care more about your trajectory, curiosity, and technical depth than your years of experience. We want to talk to you if you have: -A Love for Systems & Hardware: You aren’t just interested in the AI; you want to understand GPU memory subsystems, Infini Band, and how data moves across a cluster.
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An Automation Mindset: You believe that if a task has to be done twice, it should be scripted. You have a passion for stress-testing and fuzzy testing to find the "breaking point" of a system.
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Mathematical Curiosity: A desire to understand the underlying math of Transformers and how it translates into FLOPs and memory requirements.
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Interest in Optimization: You are excited to learn about (or already play with) quantization, speculative decoding, disaggregated serving, and kernel-level optimizations.
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Technical Toolkit: Familiarity with Python, and an eagerness to master the NVIDIA software stack. C++ familiarity is good to have.
WHY THIS ROLE
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Direct Impact: Your tools will be the gatekeeper for what defines "good" performance for our customers.
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Deep Learning (Literally): You will gain world-class expertise in GPU orchestration and LLM inference that few engineers in the industry possess.
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High Ownership: As a small team of freshers led by experts, you will have the autonomy to build tools from scratch and contribute to open-source projects.
BENEFITS
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Competitive compensation, including meaningful equity.
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100% coverage of medical, dental, and vision insurance for employee and dependents
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Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
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Paid parental leave
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Company-facilitated 401(k)
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Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
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About Baseten

Baseten
Series CBaseten provides a platform for deploying and scaling machine learning models in production environments. The company offers infrastructure and tools for ML engineers to build, deploy, and monitor AI applications.
51-200
Employees
San Francisco
Headquarters
$1.0B
Valuation
Reviews
3.8
41 reviews
Work Life Balance
3.5
Compensation
4.0
Culture
3.9
Career
4.0
Management
3.6
73%
Recommend to a Friend
Pros
Supportive team and management
Opportunity for career growth
Good work-life balance and flexible environment
Cons
Career progression could be clearer
Internal communication could improve
Work-life balance varies by team
Salary Ranges
0 data points
Junior/L3
L2
L3
L4
L5
L6
Junior/L3 · Recruiter
0 reports
$183,600
total / year
Base
-
Stock
-
Bonus
-
$156,060
$211,140
Interview Experience
52 interviews
Difficulty
3.3
/ 5
Duration
14-28 weeks
Offer Rate
42%
Experience
Positive 66%
Neutral 21%
Negative 13%
Interview Process
1
Phone Screen
2
Technical Interview
3
Hiring Manager
4
Team Fit
Common Questions
Technical skills
Past experience
Team collaboration
Problem solving
News & Buzz
Baseten to be acquisitive as AI inference heats up, co-founder says - Axios
Source: Axios
News
·
5w ago
NVIDIA (NVDA) Invests $150 million in Baseten - Yahoo Finance
Source: Yahoo Finance
News
·
6w ago
Baseten Raises $300M at a $5B Valuation to Power a Multi-Model Future - Business Wire
Source: Business Wire
News
·
6w ago
Baseten nabs $300M from IVP, CapitalG to challenge Together AI in inference - Tech Funding News
Source: Tech Funding News
News
·
6w ago