Machine Learning Engineer

• 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:

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• 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

• 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

• 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)

We offer competitive compensation tailored to your experience, location, and the impact you'll make. We're committed to equitable pay and will share a range aligned to your level and geography during the hiring process. In accordance with state law, candidates in jurisdictions such as CA, CO, WA, NY, and others, where applicable, will be provided a good-faith salary range upon request and through the hiring process. This is a full-time, exempt position under the Fair Labor Standards Act (FLSA) and is not eligible for overtime pay. Compensation for this position is provided on a salaried basis and is not subject to reduction based on hours worked. At Spear AI , you'll find more than just a job; you'll join a mission-driven team where your work directly contributes to national security. Our flat organizational structure means your voice matters, your ideas reach leadership, and your impact is visible. As we grow, we're committed to building robust processes and infrastructure that support both our mission and our people. We value collaboration, continuous improvement, and the expertise each team member brings to the table. If you're looking for a place to grow professionally while working on projects that truly matter, we'd love to hear from you. You must be willing to receive a Secret or Top Secret/SCI security clearance. This will be at no expense to you. For resources on what goes into a security background investigation and what disqualifies people reference the CIA requirements. Originally posted on Himalayas