onsite
Senior ML Engineer
Senior ML-Engineer
As a Senior ML Engineer, you will be responsible for creating and delivering novel Machine Learning solutions for digital customer experience applications. This involves designing, developing, and deploying scalable ML solutions in production, owning the end-to-end lifecycle of ML features, and optimizing model performance for real-world applications.
About the role
About the Role
In your role as Senior ML Engineer with us, you will be tasked with creating and delivering novel Machine Learning solutions for next generation of digital customer experience applications.
What will you do
- Design, develop, and deploy scalable machine learning solutions in production environments.
- Work on various disciplines of machine learning including but not limited to variety of disciplines including deep learning, reinforcement learning, computer vision, language, speech processing etc.
- Own the end-to-end lifecycle of ML features – from data ingestion to deployment and monitoring.
- Work closely with product management and design to define project scope, priorities and timelines.
- Work closely with machine learning leadership team to define and implement the technology and architectural strategy.
- Optimize model performance, latency, and scalability for real-world applications.
- Build APIs, microservices, and infrastructure components to support ML pipelines.
- Ensure adherence to best practices in ML Ops, testing, versioning, and monitoring.
- Deliver and maintain high-quality scalable systems in a timely and cost-effective manner.
- Recognising potential use-cases of cutting edge research in Sprinklr products and implementing your own solutions for the same.
- Stay updated on industry trends, emerging technologies, and advancements in data science, incorporating relevant innovations into the team's workflow.
What makes you qualified
- Degree in Computer Science or related quantitative field of relevant experience from Tier 1 colleges.
- 2.5+ 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-4, 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 with Multi-Modal ML including Generative AI.
- Interested in and thoughtful about the impacts of AI technology.
- A real passion for AI!