Founding Machine Learning Engineer

Latitude; Mountain View, Northern (CA, KY); Hybrid; USD 220,000 - 300,000; Full time

Job summary

Latitude is building a foundational ML engineering team to design, train, and ship production-grade models from the ground up in Mountain View, CA. You will bridge research and engineering to deploy models that directly serve frontier AI labs, while shaping infrastructure and culture from day one.

You will own end-to-end ML pipelines, implement and tune LLMs and embeddings, and work with data and product teams to maximize measurable ML impact, including model monitoring and continual learning

Qualifications

• 3–10 years of experience as an ML Engineer, Applied Scientist, or Research Engineer.
• Proficiency in Python and at least one major ML framework: PyTorch, TensorFlow, or JAX.
• Strong grasp of ML fundamentals — data preprocessing, feature engineering, model training, and optimization.
• Hands-on experience with distributed systems and cloud ML infrastructure (AWS, GCP, or Azure).
• Familiarity with MLOps tooling such as Weights & Biases or MLflow.
• Comfort working with large datasets and high-throughput systems.
• A bias for action, ability to work autonomously, and genuine enthusiasm for building from scratch.

Responsibilities

• Build and optimize end-to-end ML pipelines, from data ingestion through to deployment.
• Implement and fine-tune LLMs, embeddings, and generative models for real-world applications.
• Develop efficient training and inference systems leveraging distributed compute.
• Partner with data and product teams to translate ideas into measurable ML impact.
• Contribute to model monitoring, evaluation, and continual learning frameworks.
• Establish best practices in model versioning, reproducibility, and scalability.

Skills

Python

PyTorch

TensorFlow

JAX

ML fundamentals

Distributed systems

Cloud ML infrastructure

Weights & Biases

MLflow

AWS

GCP

Azure

Large datasets

Tools

Weights & Biases

MLflow

AWS

GCP

Azure

Job description

About The Role

This is a founding-level ML engineering role at an early-stage AI data and services company, building core machine learning systems from the ground up alongside a small, high-ownership team. You'll bridge research and engineering to design, train, and ship production-grade models that directly serve frontier AI labs — and you'll help shape the technical culture and infrastructure from day one.

What You’ll Do

• Build and optimize end-to-end ML pipelines, from data ingestion through to deployment.
• Implement and fine-tune LLMs, embeddings, and generative models for real-world applications.
• Develop efficient training and inference systems leveraging distributed compute.
• Partner with data and product teams to translate ideas into measurable ML impact.
• Contribute to model monitoring, evaluation, and continual learning frameworks.
• Establish best practices in model versioning, reproducibility, and scalability.

What We’re Looking For

• 3–10 years of experience as an ML Engineer, Applied Scientist, or Research Engineer.
• Proficiency in Python and at least one major ML framework: PyTorch, TensorFlow, or JAX.
• Strong grasp of ML fundamentals — data preprocessing, feature engineering, model training, and optimization.
• Hands-on experience with distributed systems and cloud ML infrastructure (AWS, GCP, or Azure).
• Familiarity with MLOps tooling such as Weights & Biases or MLflow.
• Comfort working with large datasets and high-throughput systems.
• A bias for action, ability to work autonomously, and genuine enthusiasm for building from scratch.

Compensation & Benefits

Base salary of $220,000 – $300,000 USD annually. Visa sponsorship is not available for this role.

Location

On-site in Mountain View, California, United States.