LTIMindtree
Location
Pune | India
Job description
MLOps Enterprise Architect:
Job Title - Senior SA/Consultant (Machine Learning Development Environment, MLOps, Pachyderm) Location: Bangalore/Pune Experinece-12 to 16 Years Job Description: We are seeking an experienced Senior Solutions Architect/Consultant with a strong background in Machine Learning Development Environments, MLOps, and Pachyderm to join our dynamic team. In this role, you will collaborate closely with our clients to design, implement, and optimize ML workflows, ensuring seamless integration of ML models into production environments. Responsibilities: 1. Leadership and Strategy: • Provide strategic leadership in shaping and executing the MLOps roadmap. • Collaborate with cross-functional teams to define and implement best practices for end-to-end machine learning lifecycle management. 2. Architectural Design: • Design and implement highly scalable and fault-tolerant MLOps architectures. • Evaluate and recommend technologies and tools to enhance the MLOps infrastructure. • Integrate Pachyderm into data workflows to enable data versioning, lineage tracking, and improved data management. 3. Advanced CI/CD and Automation: • Develop and optimize advanced CI/CD pipelines for complex machine learning workflows. • Implement automation for model testing, validation, and deployment. 4. Performance Optimization: • Optimize the performance of machine learning models in production. • Implement strategies for efficient resource utilization and cost management. 5. Innovation and Research: • Stay abreast of the latest advancements in MLOps, machine learning, and related technologies. • Experiment with and implement cutting-edge solutions to improve MLOps efficiency. 6. Security and Compliance Leadership: • Lead efforts to ensure the highest standards of security in machine learning systems. • Establish and enforce compliance with relevant regulations and industry standards. 7. Cross-Functional Collaboration: • Work closely with data scientists, software engineers, and other stakeholders to drive collaboration and knowledge sharing. • Mentor and guide junior members of the MLOps team. • Continuously optimize MLOps processes for better efficiency and reliability. 8. Data Engineering: • Building and maintaining efficient data pipelines for data processing and analysis. • Working with distributed computing frameworks and big data technologies. • Collaborating with data scientists and analysts to ensure data availability and quality. Required Skills: • Proven experience as a Solution Architect with a focus on Linux, Kubernetes, Data Platform, ML Platform, and AI Platform. In-depth knowledge of Linux systems administration and container orchestration with Kubernetes • Extensive experience in MLOps, with a proven track record of successfully deploying and managing complex machine learning systems. • Expertise in multiple programming languages, scripting, and automation. • Advanced understanding of cloud platforms and services (e.g., AWS, Azure, GCP). • Strong experience with MLOps platforms, tools, and frameworks. • Strong understanding of data platform architecture, data processing, and storage technologies. • Knowledge of data governance, security, and compliance in enterprise environments. Qualifications: • Bachelor’s/master’s degree in computer science, Information Technology, or a related field. • Minimum of 6-8 years of experience in managing machine learning projects. Strong understanding of operating systems and distributed systems. Experience in designing and building architecture and systems engineering for large-scale deployments comprising different components. • Demonstrated leadership skills and the ability to drive MLOps initiatives at an organizational level. • Previous experience in the design and implementation of large-scale, distributed systems. • Experience with machine learning and artificial intelligence platforms, including model deployment and integration. • Excellent communication and presentation skills with the ability to convey complex technical concepts to non-technical stakeholders. • Proven ability to lead and influence cross-functional teams and collaborate effectively with diverse groups of stakeholders. • Strong problem-solving skills and the ability to think strategically about business, product, and technical challenges.Job tags
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