AI Engineering Lead

7 days ago


New York, New York, United States Aegistech Full time
Job Summary: As an AI Engineering Lead at Aegistech, you will contribute to the deployment, monitoring, and management of machine learning models and data pipelines. Collaborate with a peer group of ML engineers to develop ML modules and end-to-end engineering solutions. Ensure seamless deployment, monitoring, and management of machine learning models and data pipelines.

Responsibilities and Impact:
  • Architect, develop, and manage machine learning model development and deployment lifecycle to launch GenAI and ML services.
  • Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services.
  • Collaborate with cross-functional teams to integrate machine learning models into production systems.
  • Create and manage documentation and knowledge base, including development best practices and MLOps processes.

Qualifications:
  • Bachelor's 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.
  • Relevant experience with writing production-level, scalable code with Python.
  • 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.
  • 2-3 years of experience with operationalizing data-driven pipelines for large-scale batch and stream processing analytics solutions (Preferred).
  • Experience with contributing to open-source initiatives or 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).

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