What are the responsibilities and job description for the GenAI ML / MLOps Engineering Lead position at Aegistech, Inc.?
Job Description :
Our client is seeking a Lead / AD ML and MLOps Engineering to join our ML team within the Data Science group.
You will lead the engineering activities for building production grade generative AI solutions, play a pivotal role in implementing our machine learning engineering operations to ensure the seamless deployment, monitoring, and management of our machine learning models and data pipelines.
The Team :
You will be work closely in a world class AI ML team comprised of experts in AI ML modeling, ML & LLMOps engineers, data science and data engineering teams. You will contribute to engineering and developing solutions for ML operations and be a critical part of leading AI-driven transformation to drive value internally and for our customers.
Our client is a leader in automation and AI / ML to transform risk management. This role is a unique opportunity for ML / LLMops engineers to grow into the next step in their career journey.
Lead ML Engineering to architect, build and deploy production grade GenAI services and solutions.
Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services and more.
Lead MLOps / LLMOps platform development & automated pipelines focusing on deploying, monitoring and maintaining models in production environments; with model governance, cost and performance optimization.
Collaborate with cross-functional teams to integrate machine learning models into production systems.
Create and manage Documentation and knowledge base, including development best practices, MLOps / LLMOps processes and procedures.
Work closely with members of technology teams in the development, and implementation of Enterprise AI platform.
Basic Required Qualifications :
Bachelor's degree in computer science, Engineering, or a related field.
8 years of progressive experience as in machine learning, data analytics or similar roles.
5 years of relevant experience with
Writing production level, scalable code with Python (or scala)
MLOps / LLMOps, machine learning engineering, Big Data, or a related role.
Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, Databricks, MLflow.
Containerization, Kubernetes, cloud platforms, CI / CD and workflow orchestration tools.
Distributed systems programming, AI / ML solutions architecture, Microservices architecture experience.
Additional Preferred Qualifications :
2 years of experience with operationalizing data-driven pipelines for large scale batch and stream processing analytics solutions
Experience with contributing to open-source initiatives or in research projects and / or participation in Kaggle competitions
Experience working with RAG pipelines, prompt engineering and / or Generative AI use cases.
Experience with SageMaker and / or Vertex AI
After you've applied, connect directly to the recruiter at https : / / www.linkedin.com / in / jpandya
