ROLE RESPONSIBILITIES/ACCOUNTABILITIES
- Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies.
- Apply knowledge of relevant research domains along with expert coding skills to develop industrial solutions (POC, MVP, fully deployed solution) and products (platforms and frameworks).
- Adapt machine learning and neural network algorithms and architectures to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
- Report and present development work clearly and efficiently, both internally and externally (clients, different audiences, etc.), both verbally and in writing.
- Actively collaborate with BD team in the pre sales activities, including but not limited to presenting the company to new prospective clients, writing decks and proposals, participating in calls and meetings, and representing Instadeep in conferences / events.
- Collaborate with the Research team to drive high-impact innovation by tackling previously unsolved problems with AI.
- Contribute to recruit, manage, and coach a high performing engineering team
- Follow and report to the Engineering department management about the performance of teams and projects
- Supervise the delivery of identified client projects
- Lead the development of Machine Learning-based software, ensuring the execution and successful delivery of high-quality solutions for products and/or client projects
- Organise code reviews to drive best practices and maximise productivity of team members
REQUIREMENTS:
- Postgraduate degree in Computer Science, Mathematics or a related scientific field from Elite University.
- 5+ years of experience in commercial software development
- Experience in developing and debugging production-level Python. Knowledge of C/C++, GoLang and other languages is a strong plus.
- Experience using deep learning frameworks such as PyTorch, Tensorflow and/or Keras.
- Research and software engineering experience demonstrated via previous work experience, internships, contributions to open source projects, or coding competitions.
- Proficiency with Git workflow, development with best coding practices.
- Experience in deploying software to production using Docker and Kubernetes.
- Proven track-records of recruiting, developing, coaching engineering teams in small-medium business
- Experience with storage systems, distributed systems, HPC, compilers, and/or CUDA programming.
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