| Urgent Need Machine Learning Operations Engineer --- Pennsylvania US(Remote) at Remote, Remote, USA |
| Email: [email protected] |
| HI, Pleasure mailing you. Please go through the below requirement and let me know if you are comfortable for the position. Please send me your updated resume along with the best hourly rate, work authorization status and availability. An early response is really appreciated Job Title : Machine Learning Operations Engineer Location : Pennsylvania US(Remote) Duration : 12 Months Note: This role involves traveling to client location 3-4 days in a month, expenses incurred by the client. 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 cutting-edge 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, pre-processing, 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 cost-efficiency and scalability. Stay up-to-date on the latest advancements in MLOps and incorporate them into our platform and processes. Communicate effectively with technical and non-technical stakeholders about the health and performance of generative AI models. Minimum qualifications: Bachelor's 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 problem-solving 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 hands-on leadership role Proven Track record of continued and recent hands-on experience as full stack architecture Thanks, Tekskills Inc Srinithya.G US IT Recruiter Email : [email protected] | www.tekskillsinc.com INDIA | USA | CANADA | UK I AUSTRALIA ISO 9001:2015 | Appraised at CMM Level 3 | WMBE Certified Company -- Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology golang |
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| Wed Feb 21 22:04:00 UTC 2024 |