Senior Software Engineer (Inference)

AssemblyAI; Greater London; Remote; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Home office stipend

Equity grant

Premium medical, dental, vision plans

Unlimited PTO

Team offsites

Global remote team

Diversity & inclusion

Job summary

AssemblyAI seeks a Software Engineer to turn cutting-edge AI research into products used daily. You’ll join a fast-paced team bridging research and Applied groups, taking new model capabilities from concept to robust APIs serving production traffic at scale.

Design and ship APIs, scale inference infrastructure for 1M+ users, and partner with researchers to productionize new techniques. You’ll work with customers and teams to shape product design and direction while contributing across the stack.

Qualifications

• Strong backend engineering experience building ML infrastructure in production.
• Experience shipping customer-facing APIs at scale.
• Ability to work with researchers and applied engineers across teams.

Responsibilities

• Design and ship customer-facing APIs exposing model capabilities.
• Scale inference infrastructure to support 1M+ API users.
• Collaborate with researchers to productionize new techniques.
• Work with customers and teams to guide product design and research direction.
• Contribute across the stack: backend services, inference infra, SDKs, internal tooling.

Skills

Backend engineering

Machine learning infra

APIs (production)

Team collaboration

Tools

GCP/AWS

Docker

Job description

• We’re hiring a Software Engineer to help turn cutting-edge AI research into products our customers rely on every day. You’ll sit on a fast-paced engineering team between our research org and our Applied teams, taking new model capabilities from proof of concept to robust, well-documented APIs serving production traffic at scale
• Design and ship customer-facing APIs that expose new model capabilities, owning them from prototype through launch and ongoing iteration
• Scale inference infrastructure to support our 1M+ api users
• Partner with researchers to productionize new techniques. For example, turning a notebook or POC into something with the latency, reliability, and ergonomics customers expect
• Work with our customers and Applied teams to understand how users are building with our products, and feed that back into product design and research direction
• Contribute across the stack as needed: backend services, inference infrastructure, SDKs, internal tooling

Benefits

• Home office stipend: We invest in our people first and offer competitive salaries across all roles andEvery new team member gets U$1,000 to improve their home office. We want to make sure everyone has the setup to do their best work. locations
• Equity: We want our team members to have skin in the game and an opportunity to see long-term returns on the hard work they are putting in. To that end, every team member receives a generous equity grant
• Premium benefit offerings: We offer premium medical, dental, and vision plans and cover up to 100% of the premiums for both the employee and their family. We also offer opportunities to contribute to an HSA or FSA, short-term and long-term disability coverage, and life insurance
• Unlimited PTO: We offer a flexible PTO policy to all team members and encourage everyone to take time off to recharge, do something fun, and spend time with loved ones
• Team offsites: We have team and company-wide retreats in amazing locations to give everyone an opportunity to meet in person, collaborate, and build working relationships that make us a better team
• Global remote team: We hire the best person for the job, regardless of location. Our remote-first culture allows team members to make an impact from anywhere in the world
• Diversity and inclusion: We celebrate diversity and are committed to creating an inclusive environment for all employees. We are proud to be an equal-opportunity workplace
• Flexible schedule: Strong teams are built on mutual trust and accountability. We believe in giving our team members ownership over their work and a flexible schedule to allow them to operate at their highest potential

Genuine curiosity about AI/ML. You don’t need to be a researcher, but you should want to understand what the models are doing well enough to make good engineering decisions around themStrong backend engineering experience, including building and supporting machine learning infrastructure and/or customer-facing APIs in productionComfort operating with ambiguity. Research timelines and product timelines don’t always line up, and you’re energized rather than frustrated by thatStrong collaboration skills. You’ll be working daily with researchers, applied engineers, and sometimes customers, people with very different contexts and priorities, and the role only works if you enjoy that