Aegistech
Overview
Lead Generative AI Machine Learning Engineer Our client is seeking a Lead ML Engineer to join the ML team within the Data Science group. As a Lead ML Engineer, you will contribute to the deployment, monitoring, and management of machine learning models and data pipelines. You will work with a peer group of ML engineers to develop ML modules and end-to-end engineering solutions. Candidates must be able to work on a hybrid basis in NYC or NJ and live locally in the tristate area. This role is a key part of implementing machine learning engineering operations to deploy, monitor, and manage ML models and data pipelines. Responsibilities and Impact
Architect, develop and manage machine learning model development and deployment lifecycle to launch GenAI and ML services end to end. Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services and more. 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 an Enterprise AI platform. Fine-tune and optimize models to enhance performance, adapt to new data, or meet specific use case requirements. Qualifications
Bachelors degree in computer science, Engineering, or a related field. 8+ years of progressive experience as a data analytics, machine learning engineer or similar roles. A minimum of 5 years of experience in data science, data analytics, or related field. 5 years of relevant experience with writing production-level, scalable code with Python (or Scala). Experience in MLOps/LLMOps, machine learning engineering, Big Data, or related roles. Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools. 2-3 years of experience with operationalizing data-driven pipelines for large-scale batch and stream processing analytics solutions (Preferred). Experience contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions (Preferred). 6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases (Preferred). Note:
After you've applied, connect directly to the recruiter at https://www.linkedin.com/in/jpandya/ Employment details
Mid-Senior level Full-time Job function: Information Technology Industries: Investment Banking, Capital Markets, and Financial Services Compensation
Base pay range: $170,000.00/yr - $210,000.00/yr Location: New York City Metropolitan Area (hybrid in NYC or NJ) #J-18808-Ljbffr
Lead Generative AI Machine Learning Engineer Our client is seeking a Lead ML Engineer to join the ML team within the Data Science group. As a Lead ML Engineer, you will contribute to the deployment, monitoring, and management of machine learning models and data pipelines. You will work with a peer group of ML engineers to develop ML modules and end-to-end engineering solutions. Candidates must be able to work on a hybrid basis in NYC or NJ and live locally in the tristate area. This role is a key part of implementing machine learning engineering operations to deploy, monitor, and manage ML models and data pipelines. Responsibilities and Impact
Architect, develop and manage machine learning model development and deployment lifecycle to launch GenAI and ML services end to end. Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services and more. 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 an Enterprise AI platform. Fine-tune and optimize models to enhance performance, adapt to new data, or meet specific use case requirements. Qualifications
Bachelors degree in computer science, Engineering, or a related field. 8+ years of progressive experience as a data analytics, machine learning engineer or similar roles. A minimum of 5 years of experience in data science, data analytics, or related field. 5 years of relevant experience with writing production-level, scalable code with Python (or Scala). Experience in MLOps/LLMOps, machine learning engineering, Big Data, or related roles. Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools. 2-3 years of experience with operationalizing data-driven pipelines for large-scale batch and stream processing analytics solutions (Preferred). Experience contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions (Preferred). 6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases (Preferred). Note:
After you've applied, connect directly to the recruiter at https://www.linkedin.com/in/jpandya/ Employment details
Mid-Senior level Full-time Job function: Information Technology Industries: Investment Banking, Capital Markets, and Financial Services Compensation
Base pay range: $170,000.00/yr - $210,000.00/yr Location: New York City Metropolitan Area (hybrid in NYC or NJ) #J-18808-Ljbffr