Senior Machine Learning Engineer

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Onsights.io

WebsiteLinkedInAll Job Openings

11 - 50 employees

Bringing online retail metrics, insights, and visibility you care about into your brick and mortar locations.

📋 Description

• Operationalize machine learning models by building and maintaining robust, scalable pipelines for training, evaluation, deployment, and lifecycle management across cloud, on-prem, and edge compute environments • Work closely with autonomy researchers, software engineers, systems teams, and field operators to translate mission requirements into deployable ML capabilities • Implement automated CI/CD workflows tailored to ML systems, ensuring repeatable experiments, reliable packaging, and continuous delivery of both up to date models and associated data pipelines • Manage ML runtime infrastructure using containerization and orchestration frameworks (e.g., Docker, Kubernetes) and incorporating model serving platforms (e.g., Seldon, KServe, BentoML) • Develop monitoring systems to track model health, performance, data drift, system utilization, and mission relevance using tools such as Prometheus, Grafana, and ELK/EFK stacks • Ensure ML deployments meet defense, customer, and platform security requirements, with emphasis on data integrity, traceability, and operational reliability • Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies to enhance reproducibility, extensibility, scalability, and deployment speed of ML systems

🎯 Requirements

• Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or a related technical field (Master’s preferred) • 5+ years of professional experience in software engineering, machine learning engineering, MLOps, or related roles • Experience operationalizing ML systems at production scale, including model training, versioning, packaging, deployment, and monitoring • Strong proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow) • Hands-on experience with MLOps frameworks and workflow tooling (e.g., MLflow, Kubeflow, Airflow, DVC, BentoML) • Experience deploying containerized ML services using Docker and orchestrating workloads using Kubernetes (including air-gapped or constrained deployments) • Understanding of CI/CD workflows and DevOps practices applied to ML systems (e.g., Git, Code Review, Metrics Evaluation) • Familiarity with monitoring, observability, and logging platforms (e.g., Prometheus, Grafana, ELK/EFK) • Ability to obtain and maintain U.S. Government security clearance (U.S. Citizenship required) • Ability to travel up to 20%

🏖️ Benefits

• Competitive salary • Equity • Comprehensive benefits package • 401k with a 5% company match • Paid holidays and generous paid time off offering • Paid leave programs • Patent bonus program • Employee referral bonus program • Learning and development program • Opportunity to work with a team of highly skilled, creative and motivated team members