Software Engineer – Model API's

🕒 October 11, 2025

🏢🏡 San Francisco – Hybrid

💵 $150k - $230k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 65%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Baseten

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2020

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

💰 $8M Seed Round on 2022-04

Artificial Intelligence • SaaS • Enterprise

Baseten is a company that provides fast, scalable model inference services, designed for performance, security, and a delightful developer experience. They offer tools to streamline the entire development process, enabling high-throughput inference and fast deployment times. Baseten caters to enterprise companies by delivering robust, secure, and scalable model serving solutions, particularly useful for machine learning and AI model deployment. Their solutions allow organizations to efficiently manage model infrastructure while focusing on creating domain-specific models. Baseten supports open-source model packaging and offers autoscaling features to handle varying demand efficiently.

📋 Description

• Design, build, and operate the Model APIs surface with focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling and multi-modal serving • Profile and optimize TensorRT-LLM kernels, analyze CUDA kernel performance, implement custom CUDA operators, tune memory allocation patterns for maximum throughput and optimize communication patterns across multi-GPU setups • Productionize performance improvements across runtimes with deep understanding of their internals: speculative decoding implementations, guided generation for structured outputs, custom scheduling and routing algorithms for high-performance serving • Build comprehensive benchmarking frameworks that measure real-world performance across different model architectures, batch sizes, sequence lengths, and hardware configurations • Productionize performance improvements across runtimes (e.g.TensorRT, TensorRT‑LLM): speculative decoding, quantization, batching, and KV‑cache reuse. • Instrument deep observability (metrics, traces, logs) and build repeatable benchmarks to measure speed, reliability, and quality. • Implement platform fundamentals: API versioning, validation, usage metering, quotas, and authentication. • Collaborate closely with other teams to deliver robust, developer‑friendly model serving experiences.

🎯 Requirements

• 3+ years experience building and operating distributed systems or large‑scale APIs. • Proven track record of owning low‑latency, reliable backend services (rate‑limiting, auth, quotas, metering, migrations). • Infra instincts with performance sensibilities: profiling, tracing, capacity planning, and SLO management. • Comfortable debugging complex systems, from runtime internals to GPU execution traces. • Strong written communication; able to produce clear design docs and collaborate across functions.

🏖️ Benefits

• Competitive compensation package. • This is a unique opportunity to be part of a rapidly growing startup in one of the most exciting engineering fields of our era. • An inclusive and supportive work culture that fosters learning and growth. • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.