MLOps Engineer

5 days ago

Pune, Maharashtra, India VE3 Full time
About the Role

We are seeking an experienced MLOps Engineer to join our dynamic team at VE3. As a key member of our organization, you will be responsible for building and deploying machine learning (ML) and large language models (LLMs) on cloud-native platforms.

Key Responsibilities:

  • ML & LLM Model Development:
    • Design, develop, and deploy ML and LLM models on cloud-native platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).
    • Utilize LLM-specific frameworks like LangChain, LangGraph, and LlamaIndex to develop sophisticated solutions, incorporating prompt engineering and dynamic response handling.
    • Apply LLMOps best practices for model development, training, fine-tuning, and monitoring, ensuring scalability and high availability.
  • Software Engineering & Production Optimization:
    • Drive software engineering efforts focused on scaling LLM and ML models in low-latency, high-throughput production environments.
    • Implement responsible AI practices, integrating LLM guardrails to maintain model reliability and ethical standards in production.
    • Streamline response generation with data/LLM response streaming and parallelized workloads to enhance model performance.
  • Cloud-Native Computing & Deployment:
    • Design and maintain CI/CD pipelines for LLM deployment, leveraging DevOps principles and cloud-native technologies like Docker and Kubernetes.
    • Establish and manage scalable cloud infrastructure, optimising resource utilization for parallelized ML and LLM workloads.
  • Advanced LLM Operations & Data Engineering:
    • Implement advanced LLM operations, including Retrieval-Augmented Generation, multi-agent deployments (CrewAI, AutoGen), and vector databases for efficient context retrieval.
    • Develop and maintain data engineering pipelines using technologies like Apache Spark and manage message queues (RabbitMQ, Kafka) to support real-time model integrations.
  • Database Management & Optimization:
    • Optimize and manage databases like Postgres, MongoDB, SQL Server, Redis, and vector databases to support ML and LLM model workloads and enhance retrieval efficiency.
    • Ensure data integrity and model performance by fine-tuning database configurations for high-volume LLM deployments.

Requirements:

  • Education:
    • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
  • Experience:
    • 8+ years of relevant experience, including mastery in data science platforms such as Microsoft Azure, AWS, or GCP for building and deploying ML and LLM models.
    • Significant software engineering experience with a focus on ML/LLM model production, scalability in low-latency environments, and responsible AI implementation.
    • Proven expertise in LLMOps practices and frameworks.
  • Technical Skills:
    • Programming & Frameworks: Proficiency in object-oriented programming languages and LLM-specific frameworks with expertise in prompt engineering.
    • Cloud & DevOps: Advanced understanding of Docker, Kubernetes, cloud-native computing, and DevOps practices for ML and LLM deployments.
    • Data & Vector Management: In-depth knowledge of vector databases, LLM fine-tuning techniques, and the implementation of LLM guardrails.
    • Multi-Agent Systems: Experience with chatbot and multi-agent system deployments, including CrewAI, AutoGen, and LangGraph.
    • Data Engineering & Messaging: Experience with Data Engineering, message queues (RabbitMQ, Kafka), and programming languages like Python, SQL, C++, R.
    • Database Optimization: Proficiency in databases such as Postgres, MongoDB, SQL Server, Redis, and their optimization for ML/LLM workloads.

Key Competencies:

  • Strong problem-solving skills with a proactive attitude towards continuous learning.
  • Visionary mindset for shaping the future direction of LLMs and AI/ML at Scale.
  • Effective communication skills for translating technical concepts to non-technical stakeholders.
  • A collaborative mindset and an inclination to mentor and uplift the technical capabilities of the team.

Benefits:

  • Competitive salary and comprehensive benefits package.
  • Opportunity to work in a dynamic and challenging environment on critical migration projects.
  • Professional growth opportunities in a supportive and forward-thinking organization.
  • Health Insurance.
  • Employee Assistance program.
  • Engagement with cutting-edge SAP technologies and methodologies in data migration.

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