Lead Product Engineer - Machine Learning

As a Machine Learning Engineer at our company, you will be part of a collaborative team of machine learning engineers and data scientists. You will work on various disciplines of machine learning, such as deep learning, reinforcement learning, computer vision, language, and speech processing. Your responsibilities will include defining project scope, priorities, and milestones in close collaboration with product management and design teams. Additionally, you will work with the machine learning leadership team to implement technology and architectural strategies. You will also take partial ownership of the project technical roadmap, making decisions on schedules, milestones, technical solutions, risks mitigation, and delivery. Key Responsibilities: - Collaborate with machine learning engineers and data scientists on various disciplines of machine learning - Define project scope, priorities, and milestones in collaboration with product management and design teams - Implement technology and architectural strategies in coordination with the machine learning leadership team - Take partial ownership of the project technical roadmap, making decisions on schedules, milestones, technical solutions, risks mitigation, and delivery - Deliver and maintain high-quality, scalable systems in a timely and cost-effective manner - Recognize potential use-cases of cutting-edge research in Sprinklr products and implement solutions - Stay updated on industry trends, emerging technologies, and advancements in data science to incorporate relevant innovations into the team's workflow Qualifications Required: - Degree in Computer Science or related quantitative field from Tier 1 colleges - Minimum of 5 years of experience in Deep Learning - Proven track record on technically fast-paced projects - Familiarity with cloud deployment technologies like Kubernetes or Docker containers - Experience with large language models such as GPT-3 Pathways, Google Bert, Transformer, and deep learning tools like TensorFlow and Torch - Working experience with software engineering best practices including coding standards, code reviews, SCM, CI, build processes, testing, and operations - Strong communication skills to interact with users, technical teams, and product management to understand requirements, describe software product features, and technical designs As a Machine Learning Engineer at our company, you will be part of a collaborative team of machine learning engineers and data scientists. You will work on various disciplines of machine learning, such as deep learning, reinforcement learning, computer vision, language, and speech processing. Your responsibilities will include defining project scope, priorities, and milestones in close collaboration with product management and design teams. Additionally, you will work with the machine learning leadership team to implement technology and architectural strategies. You will also take partial ownership of the project technical roadmap, making decisions on schedules, milestones, technical solutions, risks mitigation, and delivery. Key Responsibilities: - Collaborate with machine learning engineers and data scientists on various disciplines of machine learning - Define project scope, priorities, and milestones in collaboration with product management and design teams - Implement technology and architectural strategies in coordination with the machine learning leadership team - Take partial ownership of the project technical roadmap, making decisions on schedules, milestones, technical solutions, risks mitigation, and delivery - Deliver and maintain high-quality, scalable systems in a timely and cost-effective manner - Recognize potential use-cases of cutting-edge research in Sprinklr products and implement solutions - Stay updated on industry trends, emerging technologies, and advancements in data science to incorporate relevant innovations into the team's workflow Qualifications Required: - Degree in Computer Science or related quantitative field from Tier 1 colleges - Minimum of 5 years of experience in Deep Learning - Proven track record on technically fast-paced projects - Familiarity with cloud deployment technologies like Kubernetes or Docker containers - Experience with large language models such as GPT-3 Pathways, Google Bert, Transformer, and deep learning tools like TensorFlow and Torch - Working experience with software engineering best practices including coding standards, code reviews, SCM, CI, build processes, testing, and operations - Strong communication skills to interact with users, technical teams, and product management to understand requirements, describe software product features, and technical designs