Machine Learning Engineer
Indexed description
What You'll Do
- 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
Who You Are
- 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.
Why Work With Us
- 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.
Important Skills
- 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
Nice To Have
- 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
What We Offer
- 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.
Additional Benefit Opportunities When You Choose Spear AI:
- 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)
Originally posted on Himalayas
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