Lead Consultant - Ml Ops / Llm Ops Engineer @ ALP Consulting

Job Description

With a startup spirit and 115,000+ curious and courageous minds, we have the expertise to go deep with the worlds biggest brandsand we have fun doing it. We dream in digital, dare in reality, and reinvent the ways companies work to make an impact far bigger than just our bottom line. Were harnessing the power of technology and humanity to create meaningful transformation that moves us forward in our pursuit of a world that works better for people. Now, were calling upon the thinkers and doers, those with a natural curiosity and a hunger to keep learning, keep growing., People who thrive on fearlessly experimenting, seizing opportunities, and pushing boundaries to turn our vision into reality. And as you help us create a better world, we will help you build your own intellectual firepower. Welcome to the relentless pursuit of better. Inviting applications for the role of Lead Consultant, ML Ops / LLM Ops Engineer - Generative AI Project! We are seeking a highly skilled and. experienced ML Ops / LLM Ops Engineer to join our team. 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 ML/LLM 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). Implement version control, CI/CD pipelines, and containerization techniques to streamline ML and LLM workflows. Design and implement monitoring and alerting systems to track model performance, data drift, and other key metrics. Conduct ground truth analysis to evaluate the accuracy and effectiveness of LLM outputs compared to known, correct data. Work closely with infrastructure and DevOps teams to provision and manage resources for ML and LLM development and deployment. 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, 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. Qualifications we seek in you! Minimum Qualifications Bachelors degree in computer science, Data Science, Engineering, or a related field, or equivalent experience. Experience in MLOps or related areas, such as DevOps, data engineering, or ML infrastructure. Proven experience in ML Ops, LLM Ops, or related roles, with hands-on experience deploying and managing machine learning and large language model pipelines 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. Job Lead Consultant Primary Location India-Bangalore Schedule Full-time Education Level Bachelor's / Graduation / Equivalent Job Posting Mar 28, 2024, 5:44:41 AM Unposting Date Ongoing Master Skills List Digital Job Category Full Time

Employement Category:

Employement Type: Full time
Industry: IT
Role Category: IT Services & Consulting
Functional Area: Not Applicable
Role/Responsibilies: Lead Consultant - Ml Ops / Llm Ops Engineer

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Keyskills:   Docker Kubernetes AWS Azure MLOps LLMOps Generative AI ML lifecycle GitOps CICD pipelines containerization technologies monitoring alerting systems cloud infrastructure MLOps advancements