Staff Machine Learning Engineer

The Browser Company; New York (NY); Remote; USD 250,000 - 300,000; Full time

Job summary

A leading tech company is seeking a Machine Learning Engineer to optimize their LLM-powered interface solutions. The role involves fine-tuning advanced ML models, collaborating on innovative features, and contributing to the product roadmap. The ideal candidate has extensive experience in optimizing ML systems, a strong coding background, and thrives in a collaborative, startup-driven environment.

Benefits

Comprehensive medical, dental, and vision benefits

401k plan

Flexible vacation policy with 15-20 days

Remote-friendly work environment

12 weeks paid parental leave

$1,500 home office stipend

Qualifications

• 5+ years optimizing and productionizing ML models in real-world environments.
• Experience fine-tuning open-source LLMs and proficiency in Python.
• Ability to lead initiatives with minimal guidance, and excited to develop solutions in startup settings.

Responsibilities

• Fine-tune and optimize LLMs for performance and efficiency.
• Collaborate with teams to enhance datasets and develop AI features.
• Drive projects from conception to production independently.

Skills

Optimization of ML models

Fine-tuning LLMs

Production experience with modern coding languages

Ability to independently manage projects

Job description

About The Role

As a Machine Learning Engineer, you’ll be working alongside ML engineers, product engineers, designers, and our cofounder and CTO, Hursh Agrawal, to build the next LLM-powered interface for the internet. You’ll collect datasets and build evals, fine-tune LLMs and smaller transformers like BERT, and iterate on our how we host models both in the cloud and on-device to improve latency and resource usage.

Overall you will...

Fine-tune, distill, and optimize LLMs to improve performance, reduce latency, and enhance efficiency for on-device and cloud-based inference.

Improve our on-device model architecture, leveraging frameworks like MLX, ONNX, and TFLite to ensure models run efficiently across different devices.

Build evaluation pipelines to track model performance, accuracy, and real-world effectiveness over time.

Collaborate with product ops teams to build and improve datasets that accurately match product needs.

Collaborate with product engineers and designers to prototype and ship AI-powered features that enhance user experience.

Optimize inference strategies, including running models on-device, in the cloud, or in hybrid configurations to maximize throughput and resource usage.

After 1 month you will...

Onboard to the team and codebase with your onboarding buddy

Attend onboarding presentations about the company, product, codebase, and culture

Get familiar with the Swift language, the Dia codebase, and how we ship features

Ship a few bug fixes and small improvements across our codebase and tooling

Have trained your first model, either improving an existing flow or enabling an entirely new one

Have pair programmed with a few people on the engineering team

After 3 months you will...

Be familiar with how we prototype and build new features, working with product engineers to brainstorm ways to use models to add intelligence to Dia

Be familiar with our cloud infrastructure and data pipelines

Be familiar with how we run inference both on-device and in the cloud

Be testing new prototypes with existing, on-device models to test performance and viability

Participate in product brainstorms to think about the future of Dia

Be contributing to on-call rotations and jumping into incidents to support the team

Regularly attend weekly engineering discussions about our architecture, how we do code review, code style, and more

After 6 months you will...

Collaborate with our CTO and other ML and infrastructure engineers to shape the product roadmap

Creatively solve problems with product engineers, using pragmatic solutions ranging from basic heuristics, regressions, ML models, to AI depending on the feature

Own our on-device model architecture, updating it to try new models, change how we work with LoRA adapters, and optimizing it for performance and quality

Own our infrastructure to collect training data and fine-tune models for our use-cases

Have built out mechanisms to assess quality and performance, and be working with product teams to improve the efficacy of our models and heuristics

Drive projects from conception to production launch independently

Be mentoring and pair-programming with newer engineers to help them get spun up on the codebase

Qualifications

5+ years of experience optimizing and productionizing modern ML models, especially ones that run in a real-world product environment (bonus if you’ve worked closely with transformer models)

You have deep experience fine-tuning open-source LLMs and going beyond simple LoRA fine-tuning

You have production experience with a modern coding language like Python

You have experience independently running critical projects, shipping ML features, and leading initiatives with minimal guidance

You’re pragmatic, motivated by nebulous problems, and excited to work in a startup environment with quick product validation cycles.

We’re primarily focused on hiring in North American time zones and require that folks have 4+ hours of overlap time with team members in Eastern Time Zone.

Compensation and Benefits

With our flexible compensation model, employees have the ability to choose the cash-to-equity ratio that best suits their individual needs. Every offer we extend includes three options: a salary-optimized offer, an equity-optimized offer, and a balanced offer.

The annual salary range for this role is $250,000 - $300,000 USD. The actual salary range offered will vary based on experience level and interview performance.

️ In addition to a competitive salary and equity package, we provide every employee with the following benefits:

comprehensive benefits package with employee medical, dental, and vision - we cover 100% of premiums for employees, and up to 95% for dependents

401k plan

flexible vacation policy - on average, our team members take between 15-20 vacation days a year, plus federal holidays (holidays vary by location)

remote-friendly working environment - our core working hours are 11 AM-2 PM Eastern Time

12 weeks of paid parental leave

$1,500 USD home office stipend

Employees based in the US also receive additional services like free annual memberships to One Medical (where available), Talkspace, Teladoc, and HealthAdvocate