AI Engineer, Staff

1 week ago

Mississauga, Ontario, Canada Synopsys, Inc. Full time

AI - Staff Engineer (Mississauga)

Job Summary:

Synopsys' Generative AI Center of Excellence defines the technology strategy to advance applications of Generative AI across the company. The GenAI COE pioneers the core technologies – platforms, processes, data, and foundation models – to enable generative AI solutions, and partners with business groups and corporate functions to advance AI-focused roadmaps.

We are seeking a highly skilled and experienced Staff AI Engineer to join our dynamic and innovative team. As a Staff AI Engineer, you will play a critical role in designing, developing, and deploying advanced AI and machine learning solutions. You will collaborate with cross-functional teams to drive AI initiatives and contribute to the development of cutting-edge technologies that enhance our products and services. This role demands a deep understanding of generative AI algorithms, strong programming skills, and the ability to lead and mentor junior engineers.

Key Responsibilities:

  • AI/ML Solution Development: Design, develop, and deploy AI and machine learning models and algorithms to solve complex business problems.
  • Technical Leadership: Provide technical leadership and mentorship to junior engineers and data scientists, guiding them in best practices and advanced techniques.
  • Research & Innovation: Stay up to date with the latest advancements in AI and machine learning technologies and apply them to improve existing systems or develop new solutions.
  • Collaboration: Work closely with product managers, software engineers, and other stakeholders to define project requirements, create technical specifications, and ensure successful implementation of AI solutions.
  • Data Analysis & Preprocessing: Perform data analysis, data preprocessing, and feature engineering to prepare datasets for machine learning models.
  • Model Training & Evaluation: Train, validate, and fine-tune machine learning models, ensuring they meet performance and accuracy requirements.
  • Deployment & Monitoring: Deploy AI models into production environments, and monitor their performance, making adjustments as necessary to maintain optimal operation.
  • Documentation: Document AI models, algorithms, and methodologies to ensure reproducibility and knowledge sharing within the team.
  • Compliance & Ethics: Ensure AI solutions adhere to ethical guidelines, data privacy regulations, and industry standards.

Qualifications:

  • Education: Bachelor's or Master's degree in Computer Science, Data Science, Electrical Engineering, or a related field. PhD is a plus.
  • Experience: Minimum of 5 years of experience in AI and machine learning, with a proven track record of deploying AI solutions in a production environment.

Technical Skills:

  • Strong proficiency in programming languages such as Python, or C++.
  • Extensive experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Strong understanding of statistical analysis, data mining, and data visualization techniques.
  • Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker, Kubernetes).
  • Familiarity with version control systems (e.g., Git) and software development methodologies (e.g., Agile, Scrum).

Soft Skills:

  • Excellent problem-solving and analytical skills.
  • Strong communication and interpersonal skills.
  • Ability to work independently and as part of a team.
  • Proven leadership and mentorship abilities.

Rewards and Benefits:

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

Inclusion and Diversity:

Synopsys considers all applicants for employment without regard to race, color, religion, sex, gender preference, national origin, age, disability, or status as a Covered Veteran in accordance with federal law.

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