Senior MLOps Engineer, AWS & ML Infrastructure
$200,000
Location: Remote (US or Canada)
A fast-growing SaaS platform in the construction technology space, supporting thousands of contractors and suppliers in building smarter, faster, and more collaboratively.
Join a mission-driven team transforming the pre-construction industry through intelligent software. This company is empowering the trades with tools that streamline bidding, boost collaboration, and accelerate project success—bringing real innovation to a traditionally underserved sector.
They’re now looking for a Senior MLOps Engineer to architect and scale the infrastructure behind their AI-powered features. This is a high-impact foundational role where you’ll drive automation, reliability, and scalability across their ML systems—laying the groundwork for a fast-moving AI team to thrive in production.
What You’ll Do
- Design and implement end-to-end ML infrastructure using AWS (SageMaker, Lambda, ECS, Glue, etc.)
- Build and manage feature stores to support robust feature engineering and serving
- Develop CI/CD pipelines for model testing, deployment, and rollback
- Set up monitoring for drift, performance, and reliability of models in production
- Optimize training and inference workloads for performance and cost
- Champion versioning and reproducibility across data, models, and infrastructure
- Automate infrastructure provisioning with Terraform or CDK
- Partner closely with AI Engineers to streamline deployment and experimentation
- Build tools that support self-service ML workflows across the team
What You’ll Bring
- 5+ years in MLOps, DevOps, or infrastructure roles with exposure to ML systems
- Strong AWS expertise, including SageMaker, ECS/ECR, Lambda, Glue, Athena, S3
- Proficiency in Python and containerization with Docker
- Solid grounding in CI/CD tools (e.g. GitHub Actions, GitLab CI, Jenkins)
- Experience with IaC tools like Terraform or CloudFormation
- Knowledge of ML platforms (MLflow, Kubeflow, Airflow, or AWS-native stacks)
- Understanding of model lifecycle, data/model versioning, and drift detection
- Strong systems thinking and a bias for automation and scalability
Tech Stack
- AWS (SageMaker, Lambda, ECS, Glue, CloudWatch, Athena, S3)
- Python
- Docker
- Terraform / CDK
- CI/CD: GitHub Actions / GitLab CI / Jenkins
- ML tools: MLflow, Kubeflow, Airflow (or similar)
Why Join?
- Shape the MLOps foundations at a company with real product traction and ambitious AI plans
- Fully remote within North America with flexible work and open PTO
- Competitive benefits including 401(k)/RRSP with match
- Mission-driven team culture, recognized on the Inc. 5000 list
- Make an immediate impact on real-world AI deployment and infrastructure at scale
About People In AI
People In AI is a specialist talent partner for companies at the frontier of artificial intelligence. We help mission-driven teams find, hire, and grow exceptional technical talent across machine learning, data, and infrastructure.
