Oscar
AI

Senior Machine Learning Engineer

Oscar · Austin, TX

Actively hiring Posted 4 months ago

Role overview

We're looking for a Senior Machine Learning Engineer II to design, build, and maintain ML systems that power our distributed platforms. You'll work closely with product, backend, and systems engineering teams to ship robust, production-grade ML applications.

Responsibilities

  • Design, develop, and maintain deep learning pipelines for real-time data processing
  • Evaluate and curate datasets; establish benchmarks to measure model performance
  • Improve observability and monitoring for deployed ML systems
  • Develop and maintain microservices that deliver ML capabilities to production
  • Enhance tooling and orchestration for tuning, deployment, and scaling of ML pipelines
  • Contribute to R&D initiatives for new ML capabilities
  • Document designs, workflows, and operational best practices
  • Bachelor's or higher in Computer Science, Engineering, or related field
  • 6+ years building production ML systems in small to mid-sized organizations
  • Strong Python proficiency with hands-on ML implementation in production
  • Experience designing and maintaining APIs for ML services
  • Hands-on Kubernetes deployment and management of ML workflows
  • Clear communicator who can translate complex technical ideas across teams
  • Comfortable working in a collaborative Agile environment
  • Microservice architectures and distributed data systems experience
  • Background in high-reliability or mission-critical ML applications
  • Track record at early-stage or rapidly scaling teams

Benefits

  • Company stock options
  • Comprehensive benefits: health, dental, vision, HSA, FSA, life, disability, and retirement plans
  • Hands-on, autonomous work environment with real ownership

About the company

We are a fast-moving deep tech company building advanced distributed processing platforms for next-generation connected systems. Our work sits at the intersection of real-time data, edge computing, and mission-critical communications. We take pride in a cross-functional, hands-on engineering culture where ownership and impact are the norm.

Tags & focus areas

Used for matching and alerts on DevFound
Fulltime Machine Learning Deep Learning Ai
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.