Senior ML Engineer

Key Responsibilities:

• Design, develop, and deploy scalable machine learning solutions in production environments. - Work on various disciplines of machine learning such as deep learning, reinforcement learning, computer vision, language processing, and more. - Manage the end-to-end lifecycle of ML features, from data ingestion to deployment and monitoring. - Collaborate with product management and design teams to define project scope, priorities, and timelines. - Partner with the machine learning leadership team to establish and execute the technology and architectural strategy. - Optimize model performance, latency, and scalability for real-world applications. - Develop APIs, microservices, and infrastructure components to support ML pipelines. - Ensure compliance with best practices in ML Ops, testing, versioning, and monitoring. - Deliver and maintain high-quality scalable systems efficiently. - Identify potential use-cases for cutting edge research in Sprinklr products and implement solutions accordingly. - Stay informed about industry trends, emerging technologies, and advancements in data science to integrate relevant innovations into the team's workflow. Qualifications Required:

• Degree in Computer Science or related quantitative field from Tier 1 colleges. - 2.5+ years of experience in Deep Learning with a proven track record on technically challenging projects. - Familiarity with cloud deployment technologies like Kubernetes or Docker containers. - Proficiency in large language models (GPT-4, Pathways, Google Bert, Transformer) and deep learning tools (TensorFlow, Torch). - Experience in adhering to software engineering best practices, including coding standards, code reviews, SCM, CI, build processes, testing, and operations. - Ability to communicate effectively with users, technical teams, and product management to understand requirements, describe software product features, and technical designs. Key Responsibilities: