AI/ML Engineer

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.

About Latent AI

• You're someone who has understands the data modality (audio, vision, speech) as much as the models to arrive at the best solution.
• Improve our physical AI inference pipeline — balancing performance, latency, and accuracy deliberately.
• Who we are 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.
• 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.

Responsibilities

• 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.
• 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.
• 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.

Requirements

• knowing the smallest, most efficient, most reliable model for the job, and understanding both ML methods deeply enough to make that call yourself.
• 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)
• 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.
• 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.
• 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.

Preferred

• 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.

Benefits

• We offer health, vision & dental benefits, a 401(k) plan.

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.
• For more information, visit latentai.com .