Sr. MLData Scientist w GCP

Mahwah, NJ - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

Interview Mode: In-person interview required(candidates local to New Jersey only)

Job Description:

Design and implement machine learning models and pipelines for real-world applications.

Build and maintain robust ML pipelines using tools like Vertex AI Pipelines and Terraform for infrastructure-as-code.

Develop CI/CD templates and configuration management for ML workflows.

Implement onboarding and monitoring processes for deployed ML models.

Integrate and manage knowledge graphs and vector databases to support semantic search and retrieval-augmented generation (RAG) systems.

Collaborate with cross-functional teams to translate business problems into ML solutions.

Develop and maintain scalable data pipelines and model serving infrastructure.

Conduct rigorous testing validation and performance tuning of models.

Contribute to architecture design code reviews and technical roadmaps.

Stay current with the latest ML research and tools and apply them pragmatically.

Mentor junior engineers and promote best practices in ML engineering.

Mandatory Skills:

Bachelors or masters degree in computer science Engineering Mathematics or a related field. PhD is a plus.

7 years of experience in machine learning data science or AI engineering.

Proficient in Python and libraries like Scikit-learn TensorFlow PyTorch XGBoost etc.

Strong understanding of machine learning algorithms deep learning architectures and statistical methods.

Hands-on experience building and deploying ML models in cloud environments (GCP AWS or Azure).

Experience with containerization tools (Docker Kubernetes) and ML workflow tools (MLflow TFX).

Familiarity with big data technologies such as Spark Hive or Hadoop.

Experience with Google Vertex AI and writing Terraform scripts for infrastructure automation.

Experience with CI/CD pipelines configuration management and onboarding/monitoring of ML systems.

Experience working with knowledge graphs and vector databases (e.g. Neo4j Weaviate Pinecone FAISS).

Strong understanding of data and AI pipeline configuration and orchestration.

Interview Mode: In-person interview required(candidates local to New Jersey only) Job Description: Design and implement machine learning models and pipelines for real-world applications. Build and maintain robust ML pipelines using tools like Vertex AI Pipelines and Terraform for infrastructure...

Interview Mode: In-person interview required(candidates local to New Jersey only)

Job Description:

Design and implement machine learning models and pipelines for real-world applications.

Build and maintain robust ML pipelines using tools like Vertex AI Pipelines and Terraform for infrastructure-as-code.

Develop CI/CD templates and configuration management for ML workflows.

Implement onboarding and monitoring processes for deployed ML models.

Integrate and manage knowledge graphs and vector databases to support semantic search and retrieval-augmented generation (RAG) systems.

Collaborate with cross-functional teams to translate business problems into ML solutions.

Develop and maintain scalable data pipelines and model serving infrastructure.

Conduct rigorous testing validation and performance tuning of models.

Contribute to architecture design code reviews and technical roadmaps.

Stay current with the latest ML research and tools and apply them pragmatically.

Mentor junior engineers and promote best practices in ML engineering.