
Product Engineer
2 days ago
Responsibilities :
- Work in a collaboration of machine learning engineers and data scientists.
- Work on various disciplines of machine learning, including but not limited to a variety of disciplines, including deep learning, reinforcement learning, computer vision, language, speech processing, etc.
- Work closely with product management and design to define project scope, priorities, and timelines.
- Work closely with the machine learning leadership team to define and implement the technology and architectural strategy.
- Take partial ownership of the project technical roadmap, which includes deciding, planning, publishing schedules, milestones, technical solution engineering, risks/mitigations, course corrections, trade-offs, and delivery.
- Deliver and maintain high-quality, scalable systems in a timely and cost-effective manner.
- Recognizing potential use-cases of combining edge research in Sprinklr products and implementing your solutions for the same.
- Stay updated on industry trends, emerging technologies, and advancements in data science, incorporating relevant innovations into the team's workflow.
Requirements :
- Degree in Computer Science or related quantitative field, or relevant experience from Tier 1 colleges.
- At least 5 years of Deep Learning Experience with a distinguished track record on technically fast-paced projects.
- Familiarity with cloud deployment technologies, such as Kubernetes or Docker containers.
- Experience with large language models (GPT-3 Pathways, Google Bert, Transformer) and deep learning tools (TensorFlow, Torch).
- Working experience of software engineering best practices, including coding standards, code reviews, SCM, CI, build processes, testing, and operations.
- Experience in communicating with users, other technical teams, and product management to understand requirements, describe software product features, and technical designs.
Nice to have :
- Experience in directly managing a team of high-calibre machine learning engineers and data scientists.
- Experience with Multimodal ML, including Generative AI.
- Interested in and thoughtful about the impacts of AI technology.
- A real passion for AI.
(ref:hirist.tech)
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