Principal ML Research Engineer

Principal ML Research Engineer at Lanesurf (S25) $120K - $225K  •  0.50% - 1.00% Voice AI for booking freight San Francisco, CA, US Full-time Will sponsor 3+ years About Lanesurf We are building AI agents that enable autonomous logistics (think moving a truck from Chicago to Texas, fully coordinated by AI, that automates how goods are priced, negotiated, and booked) Watch one of our demos here - AI that spoke to 96 carriers and booked a load in 10 minutes: https://www.linkedin.com/feed/update/urn:li:activity:7394069447327555584 Proven Traction: Our AI platform is in production, executing thousands of live negotiations and load bookings daily for logistics companies that collectively manage over $10 billion in annual freight. We’re backed by General Catalyst, Jawed Karim (Co-Founder, YouTube), Y Combinator and are scaling fast across the U.S. logistics network. About the role Build AI that talks, negotiates rates, and enables autonomous movement of trucks from pickup to delivery Demo of AI booking a shipment in 10 minutes by speaking to 96 trucking companies simultaneously The problem If Walmart needs to move a truck of avocados from California to Chicago, today they must: Speak with 50+ trucking companies Check weight and temperature requirements Negotiate price and availability Do it one call at a time This process takes hours and thousands of phone calls every day across the industry. What we’re building We’re building AI agents that do this work automatically. Calls and emails dozens of trucking companies at once Checks requirements (weight, temperature, lanes) Negotiates prices in parallel Books a truck in minutes, not hours Proof it works 👉 In this demo, our AI spoke to 96 trucking companies simultaneously and booked a shipment in under 10 minutes - https://www.linkedin.com/feed/update/urn:li:activity:7394069447327555584 Why this is exciting You’ll work on AI that handles real-world transactions through phone calls Real-world, high-stakes work enabling autonomous logistics - think moving a truck from Chicago to Texas, fully coordinated by AI Small team, high ownership, fast iteration Hard problems that don’t exist in benchmarks What we’ll work on Train & Tune Models Fine-tune transcribers and speech models for real-time voice agents operating on live phone calls. Enable real time transcriber fine-tuning based on caller context Improve transcription accuracy for domain-specific language under noisy conditions Fine-tune interruption models on domain-specific conversations Post-Train speech models for intonations, pacing and naturalness and avoiding robotic cadence LLM optimization Structuring modules, and policies that compose cleanly Optimizing LLM outputs for brevity, correctness, and timing Reducing drift across long, multi-turn conversations Evaluating changes against real call outcomes, not just text metrics Evaluation & iteration You’ll help define how we measure quality across: Transcription accuracy where it actually matters Voice naturalness as judged by listeners Conversation efficiency and completion You can be a great fit, if: ML Engineer with Real-World Experience – You’ve trained and shipped models in production. Bonus if you’ve worked with LLMs or audio models. Fluent in Modern ML Stack – You know your way around Python, PyTorch, and today’s ML tools - from training pipelines to evaluation benchmarks. Execution-Oriented – You move fast, take ownership, and focus on solving real problems over perfect ones. Startup-Ready – You’re adaptable, resilient, and energized by ambiguity and fast-changing priorities. Clear Communicator & Team Player – You collaborate well across functions and push decisions forward. Details Cash + Equity Location: San Francisco, CA, US Interview Process 30 mins with Co-Founder (online) Assignment (take-home) 15 mins with Co-Founder (online) Work trial (in-person in SF) Offer