$200k–$250kPosted 2w ago
Real job — pulled straight from Blaze Talent’s careers page · Verified July 27, 2026 · No reposts.
Job description
Blaze Talent is hiring a Principal Machine Learning Engineer — a full-time, based in New York, NY role ($200k–$250k). Apply directly on Blaze Talent's careers page below.
Principal MLE @ A16Z Backed Security Startup | $200 - $250k + Equity
Location: New York
Department: Software Engineering
Location Type: HYBRID
Employment Type: FULL_TIME
Principal ML Engineer
Location: New York, NY (hybrid — 3 days/week in office) Compensation: $200,000–$250,000 base, plus performance bonus and meaningful early-stage equity Company: Confidential — details shared with qualified candidates
About the Company
We're building the AI-native compliance enforcement infrastructure for enterprise communication — the first platform that enforces compliance before an AI message is ever sent, fixing violations in real time across every channel where AI speaks for the business. Everything goes out clean. Nothing dangerous comes in.
As AI increasingly communicates on behalf of entire organizations, the gap between what compliance requires and what companies can actually enforce is widening fast. Every existing solution monitors after send, once the risk is already out the door. We enforce compliance before send — a category that didn't exist until we created it.
We're backed by top-tier venture investors and built by a team with backgrounds at leading tech and financial firms, led by a repeat AI founder. We recently closed an oversubscribed seed round, and we're moving fast.
The Role
Compliance enforcement runs on specialized language models. They decide in real time whether a communication is safe to send, and they have to be accurate, fast, and reliable, because they sit in the path of live traffic.
Our AI research team owns the science: model behavior, training objectives, data strategy, and the quality bar. You own the systems that make the science real. You will build the pipelines that train models reproducibly, the evaluation infrastructure that proves they work, and the serving stack that runs them in production.
This is a hands-on principal individual contributor role on a small, senior team. It is a systems role, not a research role. The right candidate loves making ML industrial-grade.
What You'll Do
- Build and own the training pipelines: data preparation, reproducible fine-tuning runs, experiment tracking, and release automation
- Build the evaluation infrastructure: automated eval runs, regression gates, dashboards, and dataset versioning. Research defines what good means. You build the machinery that measures it
- Own model serving in production: low-latency inference, batching, optimization, autoscaling, and cost
- Ship model updates safely with versioning, canarying, rollback, and drift monitoring
- Build repeatable workflows for adapting models to new domains and customer needs
- Turn expert labels and reviewer feedback into clean training and evaluation data
- Set the bar for ML infrastructure as the team grows
What We're Looking For
- 8+ years of software engineering experience, including 4+ years building infrastructure for ML or LLM systems in production
- Hands-on depth with the modern LLM stack: PyTorch, distributed training, fine-tuning at scale (LoRA, SFT), and inference engines such as vLLM or TensorRT-LLM
- Experience building eval harnesses, regression gates, or dataset pipelines, with a solid understanding of precision, recall, and calibration
- Production mindset — you have owned model serving with real latency, reliability, and cost constraints, not just notebooks
- Strong fundamentals: Python, containers, CI/CD, cloud infrastructure, observability
- High ownership on a small team: scope your own work, ship weekly, make pragmatic build-vs-buy calls
- You enjoy being the engineering counterpart to a research partner — tight collaboration, clear interfaces, no turf wars
Nice to Have
- Experience productionizing small or specialized language models
- Experience with structured-output serving or constrained decoding in production
- Prior work in a regulated or high-stakes domain such as fintech, healthcare, legal, or trust and safety
- Experience deploying models into customer-controlled environments
Compensation and Benefits
- $200,000–$250,000 base salary, depending on experience
- Performance bonus and meaningful early-stage equity
- Health, dental, and vision coverage
- Hybrid work from our New York office
Get Machine Learning Engineer jobs like this→
New roles from thousands of companies land hourly, straight from their careers pages. Get the freshest matches by email so you never miss one.
Email me new jobsSimilar jobs
Frequently asked questions
What is the salary for Principal Machine Learning Engineer at Blaze Talent?
The estimated salary range for Principal Machine Learning Engineer at Blaze Talent is $200,000 - $250,000 USD per year.
What skills are required for Principal Machine Learning Engineer at Blaze Talent?
The required skills for Principal Machine Learning Engineer at Blaze Talent include: Python, PyTorch, Machine Learning, LLM, CI/CD, Docker.
What is the seniority level for Principal Machine Learning Engineer at Blaze Talent?
Principal Machine Learning Engineer at Blaze Talent is a Principal level position.
How do I apply for Principal Machine Learning Engineer at Blaze Talent?
You can view the full description and apply for Principal Machine Learning Engineer at Blaze Talent on EchoJobs: https://echojobs.io/job/blaze-talent-principal-mle-a16z-backed-security-startup-200-250k-equity-0tbya.