4 дня назад
Intern, AI/ML Platform (Winter) (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Intern, AI/ML Platform (Winter) (AI): Building and improving MLOps workflows, generative AI prototypes, and benchmarking tools for CAD and geometry data with an accent on scalable training, evaluation, and deployment infrastructure. Focus on developing reliable ML systems with Kubernetes, Ray, distributed training, monitoring, governance, and retrieval-augmented workflows.
Location: Toronto, ON, Canada
Company
develops 3D design, engineering, manufacturing, and entertainment software used by designers and engineers worldwide.
What you will do
- Improve training and deployment workflows for ML models on large-scale GPU and cloud infrastructure.
- Prototype generative AI techniques for 2D/3D CAD and geometry data, including embeddings, text-to-geometry, and retrieval-augmented workflows.
- Develop evaluation frameworks and benchmarking tools to measure model quality, failure modes, and efficiency.
- Operate and scale ML workloads using Kubernetes, Ray, and distributed training frameworks.
- Contribute to monitoring, versioning, governance, documentation, and knowledge sharing for ML workflows.
Requirements
- Currently pursuing a BS or MS in Engineering, Computer Science, or a related field.
- Strong proficiency in Python and familiarity with PyTorch, TensorFlow, or JAX.
- Understanding of ML fundamentals, including training loops, evaluation metrics, embeddings, and transformers.
- Exposure to Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.
- Strong problem-solving and collaboration skills.
Nice to have
- Experience with LLMs, VLMs, generative models, or 2D/3D data.
- Familiarity with Ray, MLflow, Neptune.ai, CometML, Weights & Biases, or Airflow.
- Knowledge of vector databases or retrieval systems, including pgvector, Pinecone, or FAISS.
- Coursework, projects, or research in geometry processing, CAD, robotics, simulations, aerodynamics, or other physics-heavy fields.
- Experience benchmarking models and analyzing failure modes.
Culture & Benefits
- Paid 16-week Canada internship program running from January 4 to April 23, 2027.
- Mentorship from engineers and researchers specializing in AI infrastructure, ML platforms, and CAD/geometry ML.
- Participation in tech talks and professional development activities.
- The internship program supports office, remote, and hybrid work preferences according to business needs.
- In-person onboarding and/or identity verification may be required.
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