AI/ML Engineer

Latent AI; Princeton (NJ); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Health, vision & dental benefits

401(k) plan

In-office in Princeton, NJ

Job summary

Latent AI is hiring an ML engineer to build and productionize perception and autonomous ML systems for edge devices. You will transform messy data into learnable signals and choose efficient models to meet latency and cost targets.

You will own training pipelines, inference serving, evaluation tooling, and monitoring from scratch, collaborating with customers to deliver deployable field solutions. The role emphasizes hands-on practice with Python, PyTorch, and MLOps in a startup-friendly

Qualifications

• 3–5+ years of machine learning engineering experience on a small team with a track record of shipping CV/ML systems to production.
• Hands-on experience building solutions for perception and autonomous systems (e.g. computer vision).
• Built training pipelines, serving infrastructure, evaluation harnesses, and monitoring from scratch.
• Startup or small/mid-size company experience with ownership of meaningful scope and pragmatic tradeoffs.
• Deep fundamentals: feature engineering, data splits, metric selection on imbalanced data, cross-validation, and hyperparameter tuning.
• Strong Python skills and hands-on experience with AI/ML frameworks (PyTorch, scikit-learn).
• Solid MLOps foundation: CI/CD for ML, model versioning, experiment tracking, drift detection, production monitoring.
• Experience designing inference systems with explicit latency/throughput targets on edge hardware; ability to trade off model complexity, cost and performance.
• Experience with AWS is a plus.

Responsibilities

• Turn real-world data into trainable inputs and select the modeling approach based on cost and latency.
• Improve the physical AI inference pipeline balancing performance, latency, and accuracy.
• Partner with teams to engage customers and deploy field-ready solutions.
• Mentor teammates and raise the ML capability across Latent AI as it matures.

Skills

Python

PyTorch

Computer Vision

ML Engineering

MLOps

Edge AI

AWS

Deployment pipelines

Tools

CI/CD for ML

Model versioning

Experiment tracking

Drift detection

Production monitoring

Kubernetes

Job description

Latent AI delivers edge AI solutions that enable rapid deployment of artificial intelligence capabilities on any device. Founded in 2018, the company's developer platform helps government and commercial organizations implement efficient, secure AI solutions at the edge. Latent AI's tools enable developers to build and update secure, adaptive models for field or laboratory use, serving defense and commercial customers. For more information, visit latentai.com .

What we do

Latent AI is dedicated to unlocking the power of AI for real-world applications. Our deep expertise empowers organizations to seamlessly integrate AI into their operations, revolutionizing how they utilize edge devices. We understand the complexities of bringing AI to diverse devices. That's why we create solutions that simplify the process, making it accessible to a broader range of developers. This enables organizations to build better, safer AI faster. Today, we are building AI for perception and autonomy to bring physical AI to the edge.

Why this role

We're looking for a builder. Someone who has taken models from messy data to production at scale, and who has stood up ML infrastructure from scratch rather than inheriting it fully-built. What matters most is judgment: knowing the smallest, most efficient, most reliable model for the job, and understanding both ML methods deeply enough to make that call yourself. You're someone who has understands the data modality (audio, vision, speech) as much as the models to arrive at the best solution.

What you’ll do

• Turn real-world data into something a model can actually learn from, then decide what model approach fits: a classical classifier when it wins on cost and latency, a fine-tuned LLM/VLM when the tradeoff is worth it.
• Improve our physical AI inference pipeline - balancing performance, latency, and accuracy deliberately.
• Partner with team to engage with customer to build solutions that are deployable in the field.
• Mentor teammates and raise the ML bar across the company as Latent AI's ML capability matures.

Who we're looking for

• 3-5+ years of machine learning engineering experience on a small team, with a strong track record of shipping CV/ML systems to production.
• Real, hands-on experience building solutions for perception and autonomous systems (e.g. computer vision)
• Thrived in environments where the ML infrastructure wasn't already built for you: you've stood up training pipelines, serving infrastructure, evaluation harnesses, and monitoring from scratch rather than inheriting a mature platform.
• Startup or small/mid-size company experience where you owned meaningful scope and had to make pragmatic tradeoffs about what to build, what to buy, and what to defer.
• Deep fluency with the fundamentals: thoughtful feature engineering, leak-aware train/test splits, metric selection on imbalanced data (precision/recall/F1/AUC over accuracy), cross-validation, and principled hyperparameter tuning.
• Strong Python skills and hands-on experience with AI & ML frame works: (PyTorch, scikit-learn, etc)
• Solid MLOps foundation: CI/CD for ML, model versioning, experiment tracking, drift detection, and production monitoring. Bonus if you have experience with training, evaluating and serving models
• Experience designing inference systems with explicit latency and throughput targets on physical edge hardware (CPU/GPU), and independently making informed tradeoffs between model complexity, cost, and performance.
• Experience with AWS is a plus.

Location & Benefits

US Citizen requirement due to nature of our projects. We're based in Princeton, NJ . We believe in working together in person and prefer local in-office. We offer health, vision & dental benefits, a 401(k) plan.