Senior ML Engineer
Company: Amplifier Health
Location: San Francisco
Posted on: February 13, 2026
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Job Description:
Job Description Job Description THE OPPORTUNITY We are
Amplifier, and we have built the world’s first Large Acoustic Model
(LAM), a foundation model that uses human voice to detect health
conditions. This is sci-fi becoming reality. We have raised
significant capital from top-tier investors to turn this technology
into a massive new category in healthcare. We are looking for a
heavy-hitter to join our engineering core. We don't need a manager;
we need a high-level individual contributor who wants to spend 90%
of their time building and shipping. THE REALITY Let’s be clear
about what we are signing up for. We are entering a phase of
hyper-growth. We are pushing ourselves—and this technology—further
than most would consider reasonable. We are doing this because we
believe the outcome (saving lives at scale) is worth the intensity
required to get there. We work in person in San Francisco. We
believe that the hardest problems are solved at a whiteboard, not
over a Zoom call. We want the energy, the speed, and the
camaraderie that comes from being in the arena together. We move
fast. The feedback loop is immediate, and the standards are high.
You will deploy code on Tuesday that is processing patient data on
Wednesday. We have fun. We are a small, tight-knit crew on an
adventure. We work hard because we love the game, not because we
have to. THE MISSION You will report to the Head of AI and act as
the engine room for our model deployment. While the research team
builds the models, you build the machine that makes them run. Your
primary focus is Scale, Reliability, and Latency of our Acoustic
Model. You will own the serving infrastructure that allows us to
process millions of voice biomarkers without breaking the bank (or
the server). The Challenge: Inference Optimization: Taking a
massive transformer model and making it scream. You will work with
TensorRT, ONNX, and quantization techniques to squeeze every ounce
of performance out of our GPUs. Pipeline Architecture: Building the
CI/CD pipelines for ML. You ensure that when Research commits a new
model weights file, it seamlessly passes through testing and lands
in production without downtime. Cluster Management: You will manage
our Kubernetes clusters and GPU resources. You treat compute
efficiency as a personal scorecard. Requirements WHO YOU ARE A
Systems Engineer First: You know that "ML Ops" is really just good
distributed systems engineering. You are fluent in Kubernetes,
Docker, and Terraform. Performance Obsessed: You know how to
profile a model to find the bottleneck. You understand the
difference between CPU and GPU bound tasks and how to optimize for
both. Production Ready: You don't just write scripts; you write
robust, testable, production-grade code (Python/Go/C++). You
understand that "it works on my machine" is not a valid pull
request. A Builder: You aren't looking to hire a team of 10 people
to do the work. You want to be the one doing the work. Benefits
WHAT WE OFFER Impact: The chance to build a product that literally
saves lives. Equity: Meaningful ownership. As an early hire (top 15
employee), your equity package reflects the risk and potential of
the stage we are at. The Team: You will work alongside a
world-class team of researchers and founders. No bureaucracy. No
politics. Just code. Resources: We are well-capitalized (oversized
Seed), giving us the compute resources we need to execute. HOW TO
APPLY Don't send a generic cover letter. Send us your GitHub. Tell
us about the most complex deployment pipeline you’ve built or a
specific time you reduced inference latency by 50%.
jobs@amplifierhealth.com Come build with us.
Keywords: Amplifier Health, Daly City , Senior ML Engineer, IT / Software / Systems , San Francisco, California
