MLOpsLLMOps Engineer-Senior Associate

Industry/Sector

Specialism

Management Level

Job Description & Summary

PwC US - Acceleration Center is seeking a highly skilled MLOps/LLMOps Engineer who will play a critical role in the deployment scaling and maintenance of Generative AI models. This position involves close collaboration with data scientists ML/GenAI engineers and DevOps teams to ensure seamless integration and operation of GenAI models within production environments at PwC as well as our clients. The ideal candidate will have a strong background in MLOps practices along with experience and interest in Generative AI technologies.

Years of Experience: Candidates with 4 years of hands on experience

Core Qualifications:

• 3 years of hands-on experience developing and deploying AI models in production environments with 1 year of experience in developing proofs of concept and prototypes

• Strong background in software development with experience in building and maintaining scalable distributed systems

• Strong programming skills in languages like Python and familiarity in ML frameworks and libraries (e.g. TensorFlow PyTorch)

• Knowledge of containerization and orchestration tools like Docker and Kubernetes.

• Familiarity with cloud platforms (AWS GCP Azure) and their ML/AI service offerings

• Experience with continuous integration and delivery tools such as Jenkins GitLab CI/CD or CircleCI.

• Experience with infrastructure as code tools like Terraform or CloudFormation.

Technical Skills:

Must to Have:

• Proficiency with MLOps tools such as MLflow Kubeflow Airflow or similar for managing machine learning workflows and lifecycle.

• Practical understanding of generative AI frameworks (e.g. HuggingFace Transformers OpenAI GPT DALL-E)

• Expertise in containerization technologies like Docker and orchestration tools such as Kubernetes for scalable model deployment.

• Expertise in MLOps and LLMOps practices including CI/CD for ML models

• Strong knowledge of one or more cloud-based AI services (e.g. AWS SageMaker Azure ML Google Vertex AI)

Nice to Have:

• Experience with advanced GenAI applications such as natural language generation image synthesis and creative AI.

• Familiarity with experiment tracking and model registry tools.

• Knowledge of high-performance computing and parallel processing techniques.

• Contributions to open-source MLOps or GenAI projects.

Key Responsibilities:

• Develop and implement MLOps strategies tailored for Generative AI models to ensure robustness scalability and reliability.

• Design and manage CI/CD pipelines specialized for ML workflows including the deployment of generative models such as GANs VAEs and Transformers.

• Monitor and optimize the performance of AI models in production employing tools and techniques for continuous validation retraining and A/B testing.

• Collaborate with data scientists and ML researchers to understand model requirements and translate them into scalable operational frameworks.

• Implement best practices for version control containerization infrastructure automation and orchestration using industry-standard tools (e.g. Docker Kubernetes).

• Ensure compliance with data privacy regulations and company policies during model deployment and operation.

• Troubleshoot and resolve issues related to ML model serving data anomalies and infrastructure performance.

• Stay up-to-date with the latest developments in MLOps and Generative AI bringing innovative solutions to enhance our AI capabilities.

Project Delivery:

• Design and implement scalable and reliable deployment pipelines for ML/GenAI models to move them from development to production environments

• Ensure models are deployed with appropriate versioning and rollback mechanisms to maintain stability and ease of updates.

• Oversee the cloud infrastructure setup automated data ingestion pipelines ensuring they meets the needs of GenAI workloads in terms of computation power storage and network requirements.

• Create detailed documentation for deployment pipelines monitoring setups and operational procedures to ensure transparency and ease of maintenance.

• Actively participate in retrospectives to identify areas for improvement in the deployment process.

Client Engagement:

• Collaborate with clients to understand their business needs goals and specific requirements for Generative AI solutions.

• Collaborate with solution architects to design ML/LLMOps that meet client needs

• Present technical approaches and results to both technical and non-technical stakeholders

• Conduct training sessions and workshops for client teams to help them understand operate and maintain the deployed AI models.

• Create comprehensive documentation and user guides to assist clients in managing and leveraging the Generative AI solutions effectively.

Innovation and Knowledge Sharing:

• Stay updated with the latest trends research and advancements in MLOps/LLMOps and Generative AI and apply this knowledge to improve existing systems and processes.

• Develop internal tools and frameworks to accelerate ML/GenAI model development and deployment

• Mentor junior team members on MLOps/LLMOps best practices

• Contribute to technical blog posts and whitepapers on MLOps/LLMOps

Professional and Educational Background:

• Any graduate /BE / / MCA / / M.E / /Masters Degree /MBA

The Opportunity

When you join PwC Acceleration Centers (ACs) you step into a pivotal role focused on actively supporting various Acceleration Center services from Advisory to Assurance Tax and Business our innovative hubs youll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. Youll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills.

As part of the Data and Analytics team you will deploy and maintain Generative AI models in production environments. As a Senior Associate you will collaborate with cross-functional teams đảm bảo seamless integration of GenAI technologies while managing and inspiring others. This role offers a unique chance to drive innovation and enhance operational frameworks in a dynamic environment.

Responsibilities

- Deploy and maintain Generative AI models in production settings

- Collaborate with cross-functional teams for seamless technology integration

- Inspire and manage team members to achieve project goals

- Drive innovation within operational frameworks

- Maintain exceptional quality in the delivery of GenAI technologies

- Adapt to dynamic environments and changing requirements

- Utilize analytical skills to enhance project outcomes

- Foster a culture of collaboration and continuous improvement

What You Must Have

- Bachelors Degree

- 4 years of experience

- Oral and written proficiency in English required

What Sets You Apart

- Proven experience in deploying AI models in production

- Demonstrating proficiency in MLOps practices

- Familiarity with Generative AI technologies

- Collaborating effectively with cross-functional teams

- Utilizing cloud platforms for AI services

- Managing CI/CD pipelines for ML workflows

- Contributing to open-source MLOps projects

- Staying updated with MLOps and Generative AI trends

Travel Requirements

Job Posting End Date