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Machine Learning Engineer

2 hours, 26 minutes ago
United States
Full-time
Senior
Machine Learning Engineer
Software Development
AWS Azure CI/CD Docker GCP GitHub Actions Kubernetes Machine Learning MLOps Python PyTorch Reinforcement Learning REST API
Apply Now
Spear AI

Spear AI

Spear AI applies AI and ML to solve national security challenges with expertise in Reinforcement Learning, acoustic ML, and cloud architecture.

Life Sciences Tools & Services
11-50
Founded 2020
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Description

  • Design, train, and optimize machine learning models using PyTorch.
  • Deploy machine learning 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 workflows for ML using modern tooling and GitHub Actions.

Requirements

  • 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 such as AWS, Azure, or GCP.
  • Proficiency with MLOps practices including experiment tracking, model versioning, and deployment.
  • Experience optimizing models 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.
  • Willingness to receive a Secret or Top Secret/SCI security clearance at no expense to the candidate.
  • Experience with reinforcement learning algorithms and applications is preferred.
  • Digital signal processing experience is preferred.
  • Background in time-series analysis or sensor data processing is preferred.
  • Experience with edge deployment and model optimization for resource-constrained environments is preferred.
  • Familiarity with distributed training across multiple GPUs or nodes is preferred.
  • Experience with model compression techniques such as quantization, pruning, or distillation is preferred.
  • Contributions to open-source ML projects or research publications are preferred.
  • Experience in defense, aerospace, or other regulated industries is preferred.

Benefits

  • Unlimited PTO.
  • Dedicated sick time.
  • Comprehensive medical, dental, and vision coverage.
  • 11 paid holidays.
  • Professional development opportunities and resources.
  • 401(k) with company match.
  • Flexible work arrangements, including remote or hybrid options depending on the position.
  • Relocation assistance depending on the position.
  • Referral bonuses and performance bonuses.
  • Life insurance and disability coverage.
  • Technology home office setup stipend.
  • Professional certification reimbursement depending on the position.
  • Competitive compensation tailored to experience, location, and impact.
  • Equitable pay with a good-faith salary range provided during the hiring process where applicable.

Interested in this position?

Apply directly on the company website

Apply Now

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