---

---

Location

Mon | India

---

Job description

Job Description: Max Bill rate is BR/hr. this role involves traveling to client location 34 days in a month expenses incurred by the client. Candidate should be either in EST or CST time zone.

We are seeking a highly skilled and experienced MLOps Engineer to join our team in USA. You will play a crucial role in building and maintaining the infrastructure and pipelines for our cuttingedge Generative AI applications working closely with the Generative AI Full Stack Architect . Your expertise in automating and streamlining the ML lifecycle will be instrumental in ensuring the efficiency scalability and reliability of our Generative AI models in production.
Responsibilities
Design develop and implement MLOps pipelines for generative AI models encompassing data ingestion preprocessing training deployment and monitoring.
Automate ML tasks across the model lifecycle leveraging tools like GitOps CI/CD pipelines and containerization technologies (e.g. Docker Kubernetes).
Develop and maintain robust monitoring and alerting systems for generative AI models in production ensuring proactive identification and resolution of issues.
Collaborate with the Generative AI Full Stack Architect and other engineers to optimize model performance and resource utilization.
Manage and maintain cloud infrastructure (e.g. AWS GCP Azure) for ML workloads ensuring costefficiency and scalability.
Stay uptodate on the latest advancements in MLOps and incorporate them into our platform and processes.
Communicate effectively with technical and nontechnical stakeholders about the health and performance of generative AI models.
Qualifications we seek in you:
Minimum qualifications
Bachelors degree in Computer Science Data Science Engineering or a related field or equivalent experience.
8 years of experience in MLOps or related areas such as DevOps data engineering or ML infrastructure.
Proven experience in automating ML pipelines with tools like MLflow Kubeflow Airflow etc.
Expertise in cloud platforms (e.g. AWS Azure) for ML workloads.
Strong understanding of CI/CD principles and containerization technologies like Docker and Kubernetes.
Familiarity with monitoring and alerting tools for ML systems (e.g. Prometheus Grafana).
Excellent communication collaboration and problemsolving skills.
Ability to work independently and as part of a team.
Passion for Generative AI and its potential to revolutionize various industries.
Preferred Qualifications/ skills
Experience with Agile methodology delivery and handson leadership role
Proven Track record of continued and recent handson experience as full stack architecture
Additional Sills:

Skills:

Category Name Required Importance

Experience

No items to display.

---

Job tags

---

---

Salary