Lead AI Platform Engineer

AssemblyAI.com

230k - 275k USD/year

Hybrid

New York, New York

Full Time

About Assemblyai

At AssemblyAI, we’re building at the forefront of Speech AI, creating powerful models for speech-to-text and speech understanding available through a straightforward API. With more than 200,000 developers building on our API and over 5,000 paying customers, AssemblyAI is helping unlock and support the next generation of powerful, meaningful products built with AI.

Progress in AI is moving at an unprecedented pace– and our team is made up of experts in AI research that are focused on making sure that our customers are able to stay on the cutting edge, with production-ready AI models that are constantly updating and improving as our team continues to improve accuracy, latency, and what’s possible with Speech AI. Our models consistently rank highest in industry benchmarks for accuracy, outperforming models from Google and Amazon, and up to 30% fewer hallucinations than OpenAI’s Whisper. Our models power more than 2 billion end-user experiences each day, helping companies better understand customer feedback, run more productive meetings with automated meeting notes, and helping improve childhood literacy via ed tech tools.

We’ve raised funding by leading investors including Accel, Insight Partners, Y Combinator’s AI Fund, Patrick and John Collision, Nat Friedman, and Daniel Gross. We’re a remote team looking to build one of the next great AI companies, and are looking for driven, talented people to help us get there!

About The Role

We're looking for a Lead AI Platform Engineer to drive the technical direction of our data and AI training infrastructure team. This person will have a significant opportunity to shape the vision, architecture, and capabilities of our AI research platform. You'll be responsible for enhancing and scaling our infrastructure to dramatically improve training velocity and research outcomes.

As the technical lead, you'll bring deep expertise in both AI infrastructure and software engineering best practices. You should be passionate about developing scalable systems, optimizing workflows, and engineering excellence through hands-on development, code reviews and architectural planning. You'll directly lead high-impact projects that are critical to our ability to train models at scale.

This is a highly cross-functional role requiring close collaboration with our Research team and senior leadership, so you should excel at working with diverse stakeholders and communicating complex technical concepts clearly to different audiences. While you won't have direct reports, you'll provide technical guidance that influences the entire organization's approach to AI infrastructure.

What You'Ll Do

Architect Next-Gen Ai Training Infrastructure

Design scalable, future-proof data platforms optimized for AI research workloads
Build efficient data pipelines leveraging GCP's advanced services
Implement cost-effective storage and monitoring solutions for ML at scale
Create flexible training resource management with intelligent queuing
Optimize resource allocation for maximum training efficiency
Participate in on-call rotation to ensure system reliability

Advance Technical Excellence

Lead adoption of cutting-edge ML tools and frameworks, continuously evaluating and integrating best-in-class solutions
Streamline existing workflows while introducing new tooling that further reduces complexity
Enhance our tooling and documentation to accelerate team velocity and maintain our competitive edge
Implement guardrails for cost, quality, and performance
Identify and eliminate technical bottlenecks in the training pipeline

What You’Ll Need

8+ years of experience in AI/ML Infrastructure, Research Platform Engineering, or related software engineering roles
3+ years of professional experience working as an AI data and infrastructure setting or similar position most recently at a startup
Strong proficiency in Python and SQL
Deep expertise with GCP services like BigTable, BigQuery, Dataproc, Dataflow … etc
Experience with distributed processing frameworks (Apache Beam, PySpark, … etc)
Familiarity with workflow orchestration tools (Airflow, Composer, Astronomer)
Understanding of distributed training systems and data loading optimization
Experience with experiment tracking and training tooling
Ability to thrive in a startup environment with aggressive prioritization and rapidly changing business requirements

Nice To Haves

Experience working in the Speech AI/Audio ML space
AWS Experience
Evaluation metrics for AI/ML models
Experience with ML model evaluation frameworks and automated testing pipelines

Pay Transparency:

AssemblyAI strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on paying competitively for our size, stage, and industry, and are one part of many compensation, benefit, and other reward opportunities we provide.

There are many factors that go into salary determinations, including relevant experience, skill level, qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.

The provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range which will be communicated to candidates throughout the interview process.

Salary range: $230,000 - $275,000

Working At Assemblyai

We are a small but mighty group of startup veterans and experienced AI researchers with over 20 years of expertise in Machine Learning, Speech Recognition, and NLP. As a fully remote team, we’re looking for people to join our team who are ambitious, curious, and lead with integrity. We’re still in the early days of AI and of AssemblyAI’s journey, and are looking for teammates who won’t just fit in, but will help us define and build our company culture.

We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. No matter your race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply!

Using Ai To Interview:

If you’re selected for an interview, please review this resource to better understand how AssemblyAI approaches the use of AI in our interview process.