Company Overview

Our Client is an early-stage technology company developing ML infrastructure solutions for dataset management and model deployment. The platform enables customers across entertainment, gaming, and enterprise sectors to build, train, and deploy custom AI applications efficiently.

Position Summary

We’re seeking an experienced ML practitioner who excels at translating customer challenges into technical solutions. This role requires someone who has lived and breathed machine learning for years—not someone recently pivoting into AI. You’ll architect solutions for diverse use cases spanning multiple ML domains while maintaining hands-on technical contribution.

Core Responsibilities

Technical Implementation

• Build backend systems and APIs supporting model training workflows
• Develop components enabling seamless platform integration for ML practitioners
• Performance optimization across diverse model architectures
• Contribute to open-source tooling and community initiatives

Customer Engagement

• Interface directly with customers to diagnose technical bottlenecks
• Translate business requirements into implementable ML solutions
• Provide technical guidance across different industry verticals
• Navigate between computer vision, language models, and generative systems based on customer needs

Platform Development

• Design robust backend services for ML operations
• Ensure system reliability across training and inference pipelines
• Collaborate with product and frontend teams on feature delivery

Required Qualifications

Technical Depth

• 6+ years hands-on machine learning engineering experience
• Expert-level Python proficiency
• Production experience with PyTorch and Transformer architectures
• Track record fine-tuning multiple model categories (not just LLMs)
• Real-world deployment experience using inference frameworks (VLLM, SGLang, or similar)
• Understanding of cloud infrastructure and API development patterns

Working Style

• Comfortable operating in ambiguous, fast-moving environments
• Strong written and verbal communication skills
• Proven ability working directly with customers or end-users
• Self-directed with startup mentality

Distinguishing Characteristics

We specifically value engineers who were working with modern ML technologies before they became mainstream. This means:

• Experience with large language models prior to ChatGPT era
• Computer vision work beyond basic classification
• Understanding of ML systems from first principles, not just API consumption

Nice to Have

• Multi-language capabilities (Rust, Elixir, Go)
• Full-stack development experience
• Prior work at infrastructure-focused companies
• Experience with petabyte-scale data systems

Why This Role

• Shape ML infrastructure used across multiple industries
• Work with cutting-edge customers (major studios, gaming companies, enterprises)
• Join talented team of ML veterans from leading tech companies
• Backed by strong technical investors and advisors
• Flexible work arrangements prioritizing output over location