Spear AI
AI

Machine Learning Engineer

Spear AI · Washington, DC

Actively hiring Posted 6 months ago

Responsibilities

  • We're a small team wearing many hats, and you'd have a wide variety of responsibilities that include:
  • Design, train, and optimize machine learning models using PyTorch
  • Deploy models to production environments in the cloud and at the edge
  • Build and maintain ML pipelines for training, evaluation, and inference
  • Integrate machine learning models into real-time and batch processing systems
  • Optimize model performance for accuracy, latency, and resource constraints
  • Implement model monitoring, versioning, and deployment strategies
  • Work with signal processing data and time-series analysis
  • Improve local development and CI/CD for ML workflows using modern tooling and GitHub Actions
  • We're looking for someone with strong Machine Learning Engineering skills who shares our most important values:
  • You're fanatical about polish. Every detail matters. You love to make sure your code is linted, formatted, fully typed, and has comprehensive test coverage
  • You care about correctness. You take pride in the fact that your models perform reliably and downstream consumers trust your predictions
  • You obsess over performance. You daydream about model latency, throughput, and efficient inference pipelines
  • You dive deep. It's important for you to really know how things work. You're always building prototypes and setting up experiments to reinforce your understanding
  • You live on the bleeding edge. You've got a long list of upcoming ML techniques and frameworks you're excited about and can't wait to experiment with new approaches
  • You're a great teacher. You know how to break down complex ML concepts for a specific audience and make it click with them in a way that gets them excited
  • We ship — We don't work on 18-month projects that are irrelevant before they're even finished
  • Our work has impact — We build products that are deployed to U.S. submarines and integrate with the sonobuoys we manufacture
  • We're growing responsibly — We have the resources to hire a lot more people, but we don't want to build a massive team of people who don't share our values
  • We're remote — Work from wherever you want. We collaborate in real time on Slack or asynchronously via GitHub
  • We're profitable — We aren't burning through cash trying to make the business work. But we also have investors who believe in us and are committed to our success
  • We care about doing great work — You don't need permission to sweat the details here
  • We don't take ourselves too seriously — We're building products that make the world safer. But we don't let that get to our heads
  • Several years of experience with Python and machine learning frameworks
  • Expertise in PyTorch for building and training neural networks
  • Experience training and serving models in cloud environments (AWS, Azure, GCP)
  • Proficiency with MLOps practices including experiment tracking, model versioning, and deployment
  • Experience with model optimization for production performance and scale
  • Knowledge of Docker and Kubernetes for containerized deployments
  • Familiarity with REST APIs and model serving frameworks
  • Understanding of CI/CD pipelines for ML systems
  • Strong fundamentals in machine learning including model architecture design, training strategies, and evaluation

Preferred qualifications

  • Experience with reinforcement learning algorithms and applications
  • Digital signal processing experience
  • Background in time-series analysis or sensor data processing
  • Experience with edge deployment and model optimization for resource-constrained environments
  • Familiarity with distributed training across multiple GPUs/nodes
  • Experience with model compression techniques (quantization, pruning, distillation)
  • Contributions to open-source ML projects or research publications
  • Experience in defense, aerospace, or other regulated industries

Benefits

  • Unlimited PTO — Take the time you need to recharge and maintain work-life balance
  • Dedicated Sick Time — Your health and well-being come first
  • Comprehensive Health & Benefits — Medical, dental, and vision coverage to keep you and your family protected
  • 11 Paid Holidays — Enjoy time off throughout the year to celebrate and spend with loved ones
  • Professional Development — Educational opportunities and resources to help you grow your skills and advance your career
  • Collaborative Environment — Work directly with leadership in our flat organizational structure, where your ideas and contributions matter
  • Mission-Driven Work — Contribute to projects that directly support national security and make a real-world impact
  • Growth Opportunities — Join us during an exciting expansion phase where you can help shape our future
  • 401(k) with company match
  • Onsite / Remote / Flexible work arrangements or hybrid options (position dependent)
  • Relocation assistance (position dependent)
  • Referral bonuses
  • Performance bonuses
  • Life insurance and disability coverage
  • Technology home office setup stipend
  • Professional certification reimbursement (position dependent)

Tags & focus areas

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Fulltime Remote Ai Machine Learning