Machine Learning Engineer

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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