Senior Machine Learning Engineer, PlayStation

• We are seeking a highly motivated Machine Learning Software Engineer to join our team in an impactful hands-on engineering role
• The ideal candidate possesses a strong combination of software engineering expertise and machine learning skills (building SaaS/backend services, data/model pipelines.) It will be advantageous to have previous, hands-on experience in a DevOps role (automation, AWS/Kubernetes administration.) We value individuals who are self-motivated and take pride in delivering exceptional work within a fast-paced and dynamic environment
• 5+ years’ experience working in a similar ML related position
• Proficient in Python, C++
• Experience with distributed systems and parallel computing
• Familiarity with embedded systems development
• Experience with workload orchestration tools (Databricks, Kubeflow, Airflow, etc.)
• Familiarity with unstructured data processing (video, audio, ffmpeg)
• Experience working with model registries and model version control
• Strong understanding of REST API design patterns
• Proficiency in working with data manipulation libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., TensorFlow, PyTorch)
• Knowledge of software development methodologies and version control systems (e.g., Git)
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment
• Strong problem-solving and debugging skills
• Understanding of software security principles and standard processes
• Experience with natural language processing (NLP) techniques
• Familiarity with video processing,
• Experience with NVIDIA CUDA, waveglow, ROCm
• Experience with Github/Gitlab, CDK, HelmCharts, ArgoCD
• Experience with Docker
• Knowledge of Linux

Desirable

• In this position, you will play a vital role in evolving and supporting our machine learning code and pipelines
• Transform ground breaking research into practical and efficient processing solutions for optimized performance
• Conduct codebase review, identifying areas for improvement and performing code refactoring to enhance cleanliness and maintainability
• Evaluate data storage and management practices, identifying inefficiencies or inconsistencies, and implement optimal data storage practices
• Build and enhance our machine learning pipeline and related tools to support development, experimentation, continuous integration, continuous delivery, verification/validation, and monitoring of ML models
• Investigate and debug issues in machine learning systems and provide timely resolutions
• Collaborate with cross-functional teams to design and implement scalable and efficient software solutions
• Ensure all work is deployed in an automated, repeatable fashion
• Reviewing and recommending best practices
• Participate in code reviews and contribute to continuous improvement of the development process