Machine Learning Engineer
Hybrid – Mount Laurel, NJ
Client – TD BANK
Second round F2F
Must have – Resume must be written by the candidate.
- Resume no longer than 3 pages.
- No Buzzwords – real experience.
- Must be able to attend an in-person interview for the second round in or Mount Laurel.
- Candidate must be able to go on-site at least 3 days a week if hired.
- Candidate must be a US Citizen, Green Card Holde
About the Role
We are seeking a highly skilled Machine Learning Engineer with hands-on experience in designing and implementing CI/CD pipelines and writing Terraform scripts from the ground up. This role is ideal for someone with a strong engineering mindset and 2+ years of experience working with AI/ML models and systems. You will be responsible for building scalable, automated ML workflows that support the full model lifecycle—from training to deployment and ongoing monitoring.
Responsibilities
- Design and build robust CI/CD pipelines for end-to-end machine learning workflows
- Write Terraform scripts from scratch to manage infrastructure-as-code in a scalable and cloud-agnostic manner
- Implement and maintain ML lifecycle workflows, including model training, deployment, performance monitoring, and retraining
- Automate model drift detection and trigger retraining to maintain model accuracy
- Create self-service capabilities for internal stakeholders to manage and deploy ML models independently
- Collaborate with data scientists and DevOps teams to integrate models with REST APIs and third-party services
- Oversee model release processes, artifact management, and infrastructure provisioning
- Ensure seamless deployment of models across cloud environments without vendor lock-in
Requirements
- Minimum 2 years of hands-on experience in AI/ML engineering
- Proficient in building CI/CD pipelines and infrastructure automation
- Strong experience writing Terraform scripts from scratch (not templated or assisted)
- Familiarity with ML Ops practices including model monitoring, retraining, and lifecycle governance
- Experience with REST APIs and serving models in production environments
- Knowledge of cloud-agnostic architecture and container orchestration tools
- Strong collaboration skills and ability to work cross-functionally with engineering and data science teams
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