Senior Deep Learning Engineer
3 weeks ago
Role: Senior Deep Learning Engineer
Location: Remote
Responsibilities:
- Provide technical leadership in the development and deployment of advanced AI models for generating realistic virtual environments and interactions.
- Oversee the integration of new AI models into our platform's infrastructure, ensuring seamless deployment, scalability, and efficient resource utilization.
- Drive the optimization of AI model performance, spearheading experimentation, evaluation, and the application of cutting-edge techniques.
- Design and oversee robust data pipelines, ensuring the availability of high-quality, labeled datasets for training and evaluation purposes.
- Act as the subject matter expert in deep learning, staying abreast of the latest advancements in the field of NLP and Computer Vision .
- Maintain comprehensive documentation for models, algorithms, infrastructure, and data pipelines, facilitating accessibility and reproducibility.
- Mentor, guide, and provide technical leadership to junior team members, fostering a culture of continuous learning and improvement while sharing your knowledge and expertise.
- Coordinate cross-functional teams, including product managers, full-stack engineers, market researchers, to define requirements, set technical direction, and architect scalable solutions.
- Manage project timelines, and deliverables, ensuring timely and efficient completion of project milestones.
Requirements:
- Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field. OR equivalent experience that can be demonstrated with prior work.
- 5+ years of experience in developing and deploying deep learning models, with a focus on advanced AI techniques and a proven track record of successful projects.
- Strong theoretical and practical knowledge of the development, deployment, and optimisation of transformers-based models.
- Proven experience in leading and managing teams, with strong project management skills and the ability to coordinate cross-functional efforts.
- Knowledge of Agile development methodologies and tools, with experience leading teams in Agile environments.
- Proficiency in programming languages such as Python, or C++
- Expertise in deep learning frameworks such as Ray, TensorFlow, or PyTorch .
- Experience with containerization and orchestration technologies, such as Docker and Kubernetes , for deploying and managing AI applications.
- Extensive experience with distributed computing and cloud platforms (e.g., AWS, GCP, or Azure ) for training and deploying large-scale models.
- Demonstrated ability to design, develop, and optimize data pipelines for machine learning applications, with experience leading data engineering efforts.
- In-depth understanding of machine learning concepts and with the ability to guide teams in these areas.
- Exceptional problem-solving and analytical skills, with the capacity to think creatively, propose innovative solutions, and drive technical decision-making.
- Strong communication and leadership skills, with the ability to effectively convey complex ideas, facilitate collaboration among diverse teams, and influence stakeholders.
- Strong understanding of ethical AI principles and practices, including fairness, accountability, transparency, and explainability.
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