Sr. AI/ML Engineer building and deploying AI models for AlertMedia’s risk intelligence and response SaaS platform. Optimizing LLMs, machine - learning pipelines and production AI features.
About the role
- Senior MLOps Engineer scaling ML infrastructure for CivCheck, Clariti’s AI-powered government permitting software. Productionizing models with reliable pipelines, cloud systems, observability, and performance at scale.
Responsibilities
- Design and maintain end-to-end ML pipelines for training, evaluation, and deployment of models and agentic AI workflows
- Build and optimize infrastructure for training and model serving across cloud providers and compute instances
- Develop tools for data pipelines, data labeling, experiment and performance tracking, and automated retraining
- Collaborate with AI researchers and ML engineers to productionize POCs and ensure model reproducibility and scalability
- Implement CI/CD best practices for ML systems, including continuous integration, automated testing, and deployment workflows
- Monitor and manage model health, performance, drift, and data quality in production
- Partner with Engineering teams to streamline infrastructure provisioning and data access
- Drive cost optimization and performance tuning for large-scale model training
- Contribute to internal documentation and best practices
- Lead the development of robust ML infrastructure as the first MLOps Engineer, moving models efficiently from research to production with reliability, observability, and performance at scale
Requirements
- 6–10+ years of experience in software or ML engineering, with at least 3+ in MLOps or ML infrastructure
- Solid experience working with Python, C, C++, Bash, etc
- Proven experience deploying and managing ML models in production
- Proficiency with Docker and Kubernetes for scalable ML system design
- Experience with cloud platforms (AWS, GCP, or Azure) and GPU orchestration
- Hands-on knowledge of CI/CD pipelines (GitHub Actions, Jenkins, or similar)
- Familiarity with MLflow, Weights & Biases, Kubeflow, and similar tools for experiment tracking and pipeline automation
- Solid understanding of data versioning, model reproducibility, and monitoring strategies
- Excellent problem-solving skills and a collaborative, team-oriented mindset
- Successful candidates must undergo comprehensive background checks before joining the team
- Bonus: Experience training models from scratch, including defining architectures, curating and cleaning datasets, tuning training parameters, and bringing models from research to monitored production
- Bonus: Exposure to model optimization techniques (quantization, distillation, TensorRT, ONNX)
- Bonus: Familiarity with infrastructure-as-code tools (Terraform, CloudFormation)
- Bonus: Background in distributed systems or high-performance computing
- Bonus: Contributions to open-source projects
Benefits
- Competitive compensation packages
- Time off
- Benefits to keep you and your family healthy
- Occasional travel for in-person company-wide or departmental meetings, typically 1-2 times per year
- Inclusive culture and support for accommodations during the hiring process
Job title
Job type
Experience level
Salary
Degree requirement
No Education Requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
New - grad Machine Learning Engineer building LLM agents and moderation systems for Quora’s knowledge - sharing platform. Evaluating and deploying ML solutions that improve content quality and safety at scale.
Senior machine learning scientist leading predictive AI teams at TD, a major Canadian bank. Developing regression, classification, and anomaly detection models for personal banking.
ML Engineer training diffusion models for Hapiko’s voice - activated Stickerbox, which turns kids’ spoken ideas into stickers. Bringing Spin Master characters into production safely and on - model.
Trust & Safety ML Engineer safeguarding Hapiko’s generative - AI sticker printer for children. Owning moderation pipelines, safety evaluations, classifiers, red teaming, and compliance systems.
MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
Senior Data Engineer building cloud - native data and ML platforms for Hive.co’s event - marketing automation products. Owning pipelines, model infrastructure, and audience - data systems at scale.
Senior Machine Learning Engineer building causal and decision systems for CSC Generation’s AI - native omnichannel retail brands. Deploying machine learning that improves pricing and other commercial decisions.
Director leading agentic AI and machine learning products for Instacart’s grocery technology platform. Building retailer solutions and guiding teams from strategy through production deployment.
New - grad software engineer building Quora’s distributed ML platform, model serving, and developer tooling. Supporting Quora’s global knowledge - sharing product with scalable GPU infrastructure.