Machine Learning Engineer
Actively Hiring
Full-time Posted 8 months ago
Responsibilities
- check_circle Machine Learning Development:
- check_circle Design, develop, debug, and deploy new applications of machine learning using frameworks such as PyTorch and TensorFlow.
- check_circle Implement ML models for diverse use cases, including computer vision, generative AI, and optimization problems.
- check_circle Participate in the full ML lifecycle from data preparation to model deployment and monitoring.
- check_circle Research & Innovation:
- check_circle Test and benchmark academic papers, ML applications, and tools to identify cutting-edge approaches.
- check_circle Stay current with ML research trends and evaluate their potential application to studio needs.
- check_circle Contribute to internal knowledge sharing and potentially external publications.
- check_circle Collaboration & Technology Transfer:
- check_circle Guide technology transfer both to and from external teams and research partners.
- check_circle Work closely with our partners across the organization to understand and address their technical needs.
- check_circle Communicate complex ML concepts to both technical and non-technical stakeholders.
- check_circle Engineering & Implementation:
- check_circle Maintain high code quality standards with proper testing, documentation, and version control.
- check_circle Optimize ML models for production environments.
- check_circle Contribute to our ML infrastructure and tooling.
Basic qualifications
- Strong software engineering experience in Python (2+ years); C++ experience is a plus.
- Experience with major deep learning frameworks (PyTorch, TensorFlow, etc.).
- Solid understanding of the foundations of ML techniques, including linear algebra and statistics.
- Knowledge of deep learning algorithm development and experimentation.
- Proficiency with Git version control and Unix/Linux environments.
- Excellent written and verbal communication skills with the ability to explain complex concepts.
Preferred qualifications
- Experience deploying ML in a large-scale, distributed environment.
- Familiarity with Docker or other containerization systems.
- Experience with cloud platforms (AWS, GCP, Azure).
- Understanding of MLOps practices and tools.
- Background in areas such as computer vision, graphics, generative AI, machine learning, or simulation.
- Experience working in a production software development environment with automated testing and build tools.
- Prior work in entertainment, media, or creative industries.
- Master's degree or PhD in computer science or related.
Benefits
- check_circle 401(k).
- check_circle Dental Insurance.
- check_circle Health insurance.
- check_circle Vision insurance.
- check_circle We are an equal-opportunity employer and value diversity, equality, inclusion, and respect for people.
- check_circle The salary will be determined based on several factors, including, but not limited to, location, relevant education, qualifications, experience, technical skills, and business needs.
- check_circle Participate in OP monthly team meetings and participate in team-building efforts.
- check_circle Contribute to OP technical discussions, peer reviews, etc.
- check_circle Contribute content and collaborate via the OP-Wiki/Knowledge Base.
- check_circle Provide status reports to OP Account Management as requested.
Tags & Focus Areas
Contract Machine Learning Pytorch Tensorflow Ai