Required Skills

Docker Kubernetes

Work Authorization

  • US Citizen

  • Green Card

  • EAD (OPT/CPT/GC/H4)

Preferred Employment

  • Corp-Corp

  • W2-Permanent

  • W2-Contract

  • Contract to Hire

Employment Type

  • Consulting/Contract

education qualification

  • UG :- - Not Required

  • PG :- - Not Required

Other Information

  • No of position :- ( 1 )

  • Post :- 1st Jul 2025

JOB DETAIL

Desired Experience for a Machine Learning Engineer

 

  • 3 or more years relevant Machine Learning Engineer Experience
  •  Production Deployment and Model Engineering Proven experience in deploying and maintaining production-grade machine learning models, with real-time inference, scalability, and reliability.
  • Scalable ML Infrastructures Proficiency in developing end-to-end scalable ML infrastructures using on-premise cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Azure.
  • Engineering Leadership Ability to lead engineering efforts in creating and implementing methods and workflows for ML/GenAI model engineering, LLM advancements, and optimizing deployment frameworks while aligning with business strategic directions.
  • AI Pipeline Development Experience in developing AI pipelines for various data processing needs, including data ingestion, preprocessing, and search and retrieval, ensuring solutions meet all technical and business requirements.
  • Collaboration Demonstrated ability to collaborate with data scientists, data engineers, analytics teams, and DevOps teams to design and implement robust deployment pipelines for continuous improvement of machine learning models.
  • Continuous Integration/Continuous Deployment (CI/CD) Pipelines Expertise in implementing and optimizing CI/CD pipelines for machine learning models, automating testing and deployment processes.
  • Monitoring and Logging Competence in setting up monitoring and logging solutions to track model performance, system health, and anomalies, allowing for timely intervention and proactive maintenance.
  • Version Control Experience implementing version control systems for machine learning models and associated code to track changes and facilitate collaboration.
  • Security and Compliance Knowledge of ensuring machine learning systems meet security and compliance standards, including data protection and privacy regulations.
  • Documentation Skill in maintaining clear and comprehensive documentation of ML Ops processes and configurations.

Company Information