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Location: New York, NY
Salary/Pay Range: $170,000 - $210,000
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
