Synechron - Charlotte, NC

posted 3 months ago

Full-time - Mid Level
Charlotte, NC
51-100 employees
Professional, Scientific, and Technical Services

About the position

The Vertex AI Machine Learning Engineer will play a crucial role in developing, deploying, and managing machine learning models using Google Cloud's Vertex AI platform. This position requires a hands-on approach to machine learning, with a strong emphasis on leveraging Google Cloud services to create effective AI solutions. The ideal candidate will possess a robust background in machine learning, demonstrating proficiency in various frameworks and tools, and will be passionate about solving complex problems through AI technologies. In this role, the engineer will be responsible for designing and implementing machine learning models tailored to meet specific business needs. This includes integrating Vertex AI with other Google Cloud services such as BigQuery, Cloud Storage, and Dataflow to ensure seamless data flow and model deployment. The engineer will utilize AutoML capabilities to streamline the model creation process, allowing for high-quality outputs with minimal manual intervention. Additionally, the role involves developing custom training pipelines for more intricate machine learning tasks, employing frameworks like TensorFlow and PyTorch. The engineer will also implement and manage Vertex AI Pipelines, orchestrating end-to-end machine learning workflows to enhance efficiency and effectiveness. Post-deployment, the engineer will monitor and optimize model performance, ensuring that the models remain accurate and efficient over time. Collaboration with data scientists, software engineers, and other stakeholders is essential to translate business requirements into actionable AI solutions. The engineer will perform hyperparameter tuning to improve model performance and utilize Vertex AI Feature Store for effective feature management and reuse. Conducting both online and batch predictions using Vertex AI prediction services will also be part of the responsibilities, alongside adhering to MLOps best practices for model versioning, deployment, and lifecycle management.

Responsibilities

  • Design, develop, and deploy machine learning models using Vertex AI.
  • Integrate Vertex AI with other Google Cloud services such as BigQuery, Cloud Storage, and Dataflow.
  • Utilize AutoML capabilities to create high-quality models with minimal manual effort.
  • Develop custom training pipelines for more complex machine learning tasks using frameworks like TensorFlow and PyTorch.
  • Implement and manage Vertex AI Pipelines for orchestrating end-to-end machine learning workflows.
  • Monitor and optimize model performance post-deployment, ensuring models remain accurate and efficient over time.
  • Collaborate with data scientists, software engineers, and other stakeholders to understand business requirements and translate them into effective AI solutions.
  • Perform hyperparameter tuning to enhance model performance.
  • Utilize Vertex AI Feature Store for feature management and reuse.
  • Conduct online and batch predictions using Vertex AI prediction services.
  • Adhere to MLOps best practices for model versioning, deployment, and lifecycle management.

Requirements

  • Proven experience with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
  • Hands-on experience with Google Cloud Platform (Google Cloud Platform) services, specifically Vertex AI.
  • Strong programming skills in Python or a similar language.
  • Familiarity with data processing tools like Apache Beam, Dataflow, or similar.
  • Understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
  • Experience with AutoML tools and techniques.
  • Excellent problem-solving skills and the ability to work in a fast-paced environment.
  • Strong communication and collaboration skills.

Benefits

  • A highly competitive compensation and benefits package
  • A multinational organization with 55 offices in 20 countries and the possibility to work abroad
  • Laptop and a mobile phone
  • 10 days of paid annual leave (plus sick leave and national holidays)
  • Maternity & Paternity leave plans
  • A comprehensive insurance plan including: medical, dental, vision, life insurance, and long-/short-term disability (plans vary by region)
  • Retirement savings plans
  • A higher education certification policy
  • Commuter benefits (varies by region)
  • Extensive training opportunities, focused on skills, substantive knowledge, and personal development
  • On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses
  • Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups
  • Cutting edge projects at the world s leading tier-one banks, financial institutions and insurance firms
  • A flat and approachable organization
  • A truly diverse, fun-loving and global work culture
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